CN112396247B - Cabin check boarding rate calculation method and system - Google Patents
Cabin check boarding rate calculation method and system Download PDFInfo
- Publication number
- CN112396247B CN112396247B CN202011372647.9A CN202011372647A CN112396247B CN 112396247 B CN112396247 B CN 112396247B CN 202011372647 A CN202011372647 A CN 202011372647A CN 112396247 B CN112396247 B CN 112396247B
- Authority
- CN
- China
- Prior art keywords
- cabin
- boarding
- weight
- total
- seat
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0202—Market predictions or forecasting for commercial activities
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/40—Business processes related to the transportation industry
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Human Resources & Organizations (AREA)
- Development Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Finance (AREA)
- Accounting & Taxation (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Game Theory and Decision Science (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Data Mining & Analysis (AREA)
- Educational Administration (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The utility model discloses a cabin check boarding rate calculation method and system, which are characterized in that the boarding rate of each cabin is determined through flight seat sales data, and when team data are processed independently, the first total boarding weight, the team boarding weight and the scattered passenger boarding weight of the cabin are determined, so that the cabin check boarding rate is determined, the boarding rate in flights is determined, and the flight sales condition or the income condition can be determined or adjusted based on the boarding rate, so that the income rate of airlines is improved.
Description
Technical Field
The application relates to the field of aviation, in particular to a cabin check boarding rate calculation method and system.
Background
At present, the sales condition of the flight sold by the airline company is not analyzed and predicted, which results in that the specific sales condition of the flight cannot be correspondingly processed in the actual sales process, and the income of the airline company cannot be maximized.
Disclosure of Invention
In view of this, the present application provides a cabin check boarding rate calculation method and system, and the specific scheme is as follows:
a cabin check boarding ratio calculation method, comprising:
Determining a boarding rate for each of the bays based on the flight seat sales data;
if team data in the flight seat sales data are processed independently, determining whether the cabin section marketable seat number is the same as the allocated seat number;
if the number of the marketable seats of the cabin section is different from the allocated seats, determining a first total boarding weight of the cabin section seats in a first preset mode based on the seat allocation number;
determining a team boarding weight for the cabin class based on the first total boarding weight for the cabin class;
determining the scattered passenger boarding weight of the cabin class based on the first total boarding weight and the team boarding weight of the cabin class, and determining the total boarding weight of the cabin class based on the first total boarding weights of all cabin class classes in the cabin class;
and determining the boarding rate of the cabin node based on the scattered passenger boarding weight, the team boarding weight and the total cabin node boarding weight.
Further, the method further comprises the following steps:
if team data in the flight seat sales data are not processed independently, determining a second total boarding weight of the cabin seats in a first preset mode based on the seat allocation number and the cabin marketable seats and the allocated seats;
And determining that the team boarding weight of the cabin berth is 0, and simultaneously determining the second total boarding weight of the cabin berth as the scattered passenger total boarding weight of the cabin berth.
Further, the method further comprises the following steps:
and if team data in the flight seat sales data are processed independently, determining a first total boarding weight of the cabin class in a second preset mode based on the current cabin class limiting requirement and the current cabin class limiting requirement in the flight seat sales data.
Further, the method further comprises the following steps:
if team data in the flight seat sales data are not processed independently, determining a second total boarding weight of the cabin class in a second preset mode based on the current cabin class limiting requirement and the current cabin class limiting requirement;
and determining that the team boarding weight of the cabin berth is 0, and simultaneously determining the second total boarding weight of the cabin berth as the scattered passenger total boarding weight of the cabin berth.
Further, the determining the boarding rate of the cabin section based on the scattered passenger boarding weight, the team boarding weight, and the total cabin section boarding weight includes:
determining the product of the boarding weight of the visitor and the boarding probability of the visitor as a first value, and determining the product of the boarding weight of the team and the boarding probability of the team as a second value;
And determining the ratio of the sum of the first value and the second value to the total boarding weight of the cabin section as the boarding rate of the cabin section.
Further, the method further comprises the following steps:
determining whether the cabin check boarding rate is less than a first preset value;
and if the cabin check boarding rate is smaller than the first preset value, adjusting the cabin check boarding rate.
Further, the method further comprises the following steps:
and determining the standard deviation of the boarding rate of the cabin section based on the scattered boarding weight and the team boarding weight of the cabin section.
A cabin check boarding ratio calculation system, comprising:
a first determination unit for determining a boarding rate of each of the bays based on the flight seat sales data;
a second determining unit for determining whether the cabin section marketable seat number is the same as the allocated seat number when team data in the flight seat sales data are processed separately;
a third determining unit configured to determine a first total boarding weight for the cabin class in the first preset mode based on the number of seat assignments when it is determined that the number of marketable seats of the cabin class is different from the number of assigned seats;
a fourth determining unit configured to determine a team boarding weight of the cabin space based on a first total boarding weight of the cabin space;
A fifth determining unit, configured to determine a loose boarding weight of the cabin space based on the first total boarding weights of all the cabin spaces in the cabin space and the team boarding weights, and determine the total boarding weight of the cabin space based on the first total boarding weights of all the cabin spaces in the cabin;
and a sixth determining unit for determining the boarding rate of the cabin section based on the scattered passenger boarding weight, the team boarding weight and the total boarding weight of the cabin section.
Further, the method further comprises the following steps:
a seventh determining unit configured to determine, when team data in the flight seat sales data is not processed separately, a second total boarding weight for the cabin class in a first preset mode based on a seat allocation number and a cabin marketable seat number and an allocated seat number; and determining that the team boarding weight of the cabin berth is 0, and simultaneously determining the second total boarding weight of the cabin berth as the scattered passenger total boarding weight of the cabin berth.
Further, the method further comprises the following steps:
and an eighth determining unit, configured to determine, when team data in the flight seat sales data is processed separately, a first total boarding weight of the cabin class in the second preset mode based on the current cabin class restriction requirement and the current cabin class restriction requirement in the flight seat sales data.
According to the technical scheme, the boarding rate calculation method and the boarding rate calculation system for the cabin section disclosed by the application are used for determining the boarding rate of each cabin position in the cabin section based on the flight seat sales data, if the team data in the flight seat sales data are processed independently, whether the marketable seat number of the cabin section is the same as the allocated seat number or not is determined, if the marketable seat number is different, the first total boarding weight of the cabin section in the first preset mode is determined based on the seat allocation number, the team boarding weight of the cabin section is determined based on the first total boarding weight of the cabin section, the scattered passenger boarding weight of the cabin section is determined based on the first total boarding weight of the cabin section and the team boarding weight, and meanwhile, the total boarding weight of the cabin section is determined based on the scattered passenger boarding weight, the team boarding weight and the total boarding weight of the cabin section. According to the method, the boarding rate of each cabin is determined through the flight seat sales data, and when team data are processed independently, the first total boarding weight, the team boarding weight and the scattered passenger boarding weight of the cabin are determined, so that the boarding rate of the cabin is determined, the boarding rate of flights is determined, and the flight sales condition or the income condition can be determined or adjusted based on the boarding rate, so that the income rate of airlines is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a cabin check boarding rate calculation method disclosed in an embodiment of the present application;
fig. 2 is a flowchart of a cabin check boarding rate calculation method disclosed in an embodiment of the present application;
fig. 3 is a schematic structural diagram of a cabin check boarding ratio calculation system according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
The application discloses a cabin check boarding rate calculation method, a flow chart of which is shown in fig. 1, comprising the following steps:
step S11, determining the boarding rate of each cabin in the cabin based on the flight seat sales data;
cabin sections represent divisions of a flight shelter, such as: the flight has two levels of cabin, namely a official cabin and an economic cabin, and the cabin sections are divided into two corresponding cabin sections, namely the official cabin section and the economic cabin section. The bay section contains different sub-bays, and the flight sales are priced by the bays. The public service cabin comprises a cabin position which can be formed by: the economy cabin comprises a Y cabin, a B cabin, an M cabin and an H cabin, the different cabins also correspond to different prices, and the cabin section is the total set of all cabins.
The boarding probabilities for each of the bunkers can be determined based on the flight seat sales data so that calculation of the boarding probabilities for the bunkers can be achieved based on the boarding rate for each of the bunkers.
Step S12, if team data in the flight seat sales data are processed independently, determining whether the cabin section marketable seat number is the same as the allocated seat number;
the flight seat sales data comprises team data and loose-subscriber data, namely, the seats sold by the flights can have team tickets and loose-subscriber tickets, and when the boarding rate of the cabin is calculated, all the tickets can be calculated uniformly, namely, whether the team tickets or the loose-subscriber tickets are purchased is not distinguished; the team ticket purchase and the loose customer ticket purchase can be calculated respectively. The unified calculation of all the tickets is different from the two calculation modes of distinguishing the team ticket purchase from the bulk ticket purchase.
If team data in the flight seat sales data are processed separately, namely, the team ticket purchase is distinguished from the loose passenger ticket purchase, and the team ticket purchase is calculated respectively, whether the cabin section marketable seat number is the same as the allocated seat number needs to be determined first.
If the number of marketable seats of the bay is the same as the number of allocated seats, it is indicated that all allocated seats in the bay have been marketable, and at this time, it may be determined that the total boarding weight of the bay and the scattered boarding weight of the bay are the same as the team boarding weight of the bay, and the first preset value may be 0.
In this case, the boarding ratio of the cabin is 100, and the standard deviation of the boarding ratio of the cabin is 0.
If the number of marketable seats of the bay is different from the number of allocated seats, it is indicated that all allocated seats in the bay are partially not marketable, and at this time, a first total boarding weight for the bay in the first preset mode needs to be determined based on the number of seat allocation.
Step S13, if the marketable seats of the cabin section are different from the allocated seats, determining a first total boarding weight of the cabin section seats in a first preset mode based on the seat allocation numbers;
the first preset mode may be: a split processing mode. The separation processing mode is a seat allocation mode after the optimization processing by an optimization center of the system.
The seats in this seat allocation mode can only allocate their own class and cannot mix. Such as: the protection number of the 8-fold bunk is 10, after the 7-fold bunk is sold, only the seat of the 8-fold bunk can be sold, and the seat in the 8-fold bunk cannot be sold in a 7-fold seat standard by virtue of the seat in the 8-fold bunk. The protection number of the bunkers refers to seats which are fixedly distributed by each bunk and do not allow other bunkers to borrow and sell.
The seat allocation number is the protection number of the cabin by an EMSR A method in a separation processing mode.
EMSR a is a computational model that expects maximization of marginal seat benefit, comprising: only the separate process model to the own class is protected, and the nested process model across classes can be performed.
Determining a first total boarding weight of the cabin class in a first preset mode based on the seat allocation number, wherein the first total boarding weight is specifically as follows: the difference between the marketable seat number of the cabin segment and the total empty seat allocation number of the cabin segment is determined, and the quotient between the seat allocation number and the difference is determined as the total boarding weight of the cabin segment.
Namely: total boarding weight for bay = number of seat assignments/(number of marketable seats for bay-total number of empty seats for bay).
Step S14, determining the team boarding weight of the cabin space based on the first total boarding weight of the cabin space;
The team boarding weight of the cabin class is determined, the determination can be performed based on the current final booking number of the team in the cabin class, specifically, the difference between the saleable seat number of the cabin class and the total empty seat allocation number of the cabin class is determined, and the quotient between the current final booking number of the team and the difference is determined as the team boarding weight.
In addition, it may be:
team boarding weight = Min (first total boarding weight for the bay level, the current final booking number of the team/(bay marketable seat number-bay total empty seat allocation number)).
That is, the minimum value between the first total boarding weight of the cabin space and the current final booking number of the team/(the cabin marketable seat number-the cabin total empty seat allocation number) is determined as the team boarding weight.
Step S15, determining the scattered passenger boarding weights of the cabin class based on the first total boarding weights of the cabin class and the team boarding weights, and determining the total boarding weights of the cabin class based on the first total boarding weights of all the cabin class in the cabin class;
the scattered passenger boarding weight of the cabin class, namely the difference between the first total boarding weight of the cabin class and the team boarding weight, is determined based on the determined first total boarding weight and team boarding weight.
Since a bay is made up of a plurality of bays in the bay, the total boarding weight of the bay is equal to the sum of the total boarding weights of all bays in the bay.
Namely: total boarding weight of bay = Σtotal boarding weight of bay.
And S16, determining the boarding probability of the cabin based on the boarding weight of the scattered passengers and the boarding weight of the team and the total boarding weight of the cabin.
The boarding probability of the cabin is related to the boarding weight of the scattered passengers, the boarding weight of the team and the total boarding weight of the cabin, and the boarding rate of the cabin can be obtained by carrying out weighted summation on the boarding weight of the scattered passengers and the boarding weight of the team of each cabin in the cabin and then carrying out averaging. Thus, determining the cabin node probability may be accomplished according to the following:
determining the product of the boarding weight of the visitor and the boarding probability of the visitor as a first value, and determining the product of the boarding weight of the team and the boarding probability of the team as a second value; and determining the ratio of the sum of the first value and the second value to the total boarding weight of the cabin section as the boarding probability of the cabin section.
Further, the cabin check boarding ratio standard deviation may be calculated simultaneously with the cabin check boarding ratio calculation.
And determining the standard deviation of the boarding rate of the cabin section based on the scattered boarding weight and the team boarding weight of the cabin section.
Specifically, cabin check boarding ratio standard deviation= (boarding weight of loose passenger x boarding ratio standard deviation = (sigma)) 2 ++ (team boarding weight x team boarding Rate Standard deviation) 2 ]﹜ 1/2 。
In addition, it may further include:
after the check boarding rate is determined, determining whether the check boarding rate is smaller than a first preset value, and if the check boarding rate is smaller than the first preset value, adjusting the check boarding rate so that the adjusted check boarding rate reaches the first preset value.
Specifically, the first preset value may be 50%.
According to the method for calculating the boarding rate of the cabin section, the boarding rate of each cabin position in the cabin section is determined based on the flight seat sales data, if team data in the flight seat sales data are processed independently, whether the marketable seat number of the cabin section is the same as the allocated seat number or not is determined, if the marketable seat number is different, the first total boarding weight of the cabin section cabin position in the first preset mode is determined based on the seat allocation number, the team boarding weight of the cabin section cabin position is determined based on the first total boarding weight of the cabin section cabin position, the loose passenger boarding weight of the cabin section is determined based on the first total boarding weight of all cabin section cabin positions in the cabin section, and the boarding rate of the cabin section is determined based on the loose passenger boarding weight, the team boarding weight and the total boarding weight of the cabin section. According to the method, the boarding rate of each cabin is determined through the flight seat sales data, and when team data are processed independently, the first total boarding weight, the team boarding weight and the scattered passenger boarding weight of the cabin are determined, so that the boarding rate of the cabin is determined, the boarding rate of flights is determined, and the flight sales condition or the income condition can be determined or adjusted based on the boarding rate, so that the income rate of airlines is improved.
The embodiment discloses a cabin check boarding rate calculation method, a flow chart of which is shown in fig. 2, comprising the following steps:
step S21, determining the boarding rate of each cabin in the cabin based on the flight seat sales data;
step S22, if team data in the flight seat sales data are processed independently, determining whether the cabin section marketable seat number is the same as the allocated seat number;
step S23, if the marketable seats of the cabin section are different from the allocated seats, determining a first total boarding weight of the cabin section seats in a first preset mode based on the seat allocation numbers;
step S24, determining the team boarding weight of the cabin space based on the first total boarding weight of the cabin space;
step S25, determining the scattered passenger boarding weights of the cabin class based on the first total boarding weights of all the cabin class boards in the cabin class and the team boarding weights, and determining the total boarding weights of the cabin class based on the first total boarding weights of all the cabin class boards in the cabin class;
step S26, if team data in the flight seat sales data are not processed independently, determining a second total boarding weight of the cabin seats in the first preset mode based on the seat allocation number, the cabin marketable seat number and the allocated seat number;
Step S27, determining that the team boarding weight of the cabin class is 0, and simultaneously determining the second total boarding weight of the cabin class as the scattered passenger total boarding weight of the cabin class, and determining the total boarding weight of the cabin class based on the first total boarding weights of all the cabin class classes in the cabin class;
and S28, determining the boarding probability of the cabin based on the boarding weight of the scattered passengers and the boarding weight of the team and the total boarding weight of the cabin.
If team data in the flight seat sales data are not processed independently, all data in the flight seat sales data are processed according to the loose passenger, at the moment, no team boarding weight exists, the team boarding weight can be directly determined to be 0, and correspondingly, when the team boarding weight is 0, the loose passenger boarding weight is the second total boarding weight of the cabin.
The second total boarding weight for the cabin class may be determined by determining the second total boarding weight for the cabin class in the first preset mode based on the number of seat assignments and the number of cabin class marketable seats and the number of assigned seats.
Determining a second total boarding weight of the cabin class in the first preset mode based on the number of seat allocation, wherein the second total boarding weight is specifically as follows: the difference between the marketable seat number of the cabin segment and the total empty seat allocation number of the cabin segment is determined, and the quotient between the seat allocation number and the difference is determined as the total boarding weight of the cabin segment.
Namely: total boarding weight for bay = number of seat assignments/(number of marketable seats for bay-total number of empty seats for bay).
Wherein the second total boarding weight for determining the cabin class is the same as the first total boarding weight for determining the cabin class, but is determined under different preconditions.
After the second total boarding weight and the first total boarding weight are determined, the team boarding weight and the scattered boarding weight under different conditions are respectively determined, and then the cabin boarding probability is determined based on the same steps.
Further, the cabin check boarding rate calculation method disclosed in the embodiment may further include:
if team data in the flight seat sales data are not processed independently, determining a second total boarding weight of the cabin class in a second preset mode based on the current cabin class limiting requirement and the current cabin class limiting requirement; and determining that the team boarding weight of the cabin berth is 0, and simultaneously determining the second total boarding weight of the cabin berth as the scattered passenger total boarding weight of the cabin berth.
In the case where team data in the flight seat sales data is not processed separately, if the first preset mode is adopted, the processing is performed by adopting the above embodiment, and if the first preset mode is not adopted, but the second preset mode is adopted, the second total boarding weight needs to be determined based on the current cabin class restriction requirement and the current cabin class restriction requirement.
Wherein, the flight seat sales data comprises: current cabin class restriction requirements and current cabin class restriction requirements, specifically:
second total boarding weight = current cabin class restriction requirement/current cabin class restriction requirement.
I.e. the quotient between the current cabin class restriction requirement and the current cabin class restriction requirement is the second total boarding weight.
After the second total boarding weight of the current cabin is determined, the determination of the total boarding weight of the cabin and the boarding rate of the cabin is continued based on the scheme.
Further, the cabin check boarding rate calculation method disclosed in the embodiment may further include:
if team data in the flight seat sales data are processed independently, determining a first total boarding weight of the cabin class in a second preset mode based on the current cabin class limiting requirement and the current cabin class limiting requirement in the flight seat sales data.
If the team data in the flight seat sales data is processed separately, if the first preset mode is adopted, the processing is performed by adopting the embodiment, and if the first preset mode is not adopted, but the second preset mode is adopted, the first total boarding weight needs to be determined based on the current cabin class restriction requirement and the current cabin class restriction requirement.
At this time, the first boarding weight is: the quotient between the current cabin class restriction requirement and the current cabin class restriction requirement, i.e. the first total boarding weight = current cabin class restriction requirement/current cabin class restriction requirement.
And under the condition that the team data are processed independently in the second preset mode, determining the team boarding weight of the cabin after determining the first total boarding weight. Specific:
first total boarding weight = Min (total boarding weight restrictive demand, current crew bunk restrictive demand/current bunk restrictive demand).
After the team boarding weights of the bunkers are determined, the scattered passenger boarding weights of the bunkers are continuously determined based on the above embodiments, and the total boarding weights of the bunkers and the boarding rate of the bunkers are further determined.
According to the method for calculating the boarding rate of the cabin section, the boarding rate of each cabin position in the cabin section is determined based on the flight seat sales data, if team data in the flight seat sales data are processed independently, whether the marketable seat number of the cabin section is the same as the allocated seat number or not is determined, if the marketable seat number is different, the first total boarding weight of the cabin section cabin position in the first preset mode is determined based on the seat allocation number, the team boarding weight of the cabin section cabin position is determined based on the first total boarding weight of the cabin section cabin position, the loose passenger boarding weight of the cabin section is determined based on the first total boarding weight of all cabin section cabin positions in the cabin section, and the boarding rate of the cabin section is determined based on the loose passenger boarding weight, the team boarding weight and the total boarding weight of the cabin section. According to the method, the boarding rate of each cabin is determined through the flight seat sales data, and when team data are processed independently, the first total boarding weight, the team boarding weight and the scattered passenger boarding weight of the cabin are determined, so that the boarding rate of the cabin is determined, the boarding rate of flights is determined, and the flight sales condition or the income condition can be determined or adjusted based on the boarding rate, so that the income rate of airlines is improved.
The embodiment discloses a cabin check boarding ratio calculation system, the structure schematic diagram of which is shown in fig. 3, comprising:
a first determination unit 31, a second determination unit 32, a third determination unit 33, a fourth determination unit 34, a fifth determination unit 35, and a sixth determination unit 36.
Wherein the first determination unit 31 determines a boarding rate of each of the bays based on the flight seat sales data;
the second determination unit 32 determines whether or not the cabin section marketable seat count is the same as the allocated seat count when team data in the flight seat sales data is handled alone;
the third determination unit 33 determines a first total boarding weight for the cabin class in the first preset mode based on the seat allocation number when it is determined that the cabin class marketable seat number is different from the allocated seat number;
the fourth determination unit 34 determines a team boarding weight of the cabin class based on the first total boarding weight of the cabin class;
the fifth determination unit 35 determines the scattered boarding weights of the boarding seats of the cabin based on the first total boarding weights and the team boarding weights of the boarding seats of the cabin, and determines the total boarding weights of the cabin based on the first total boarding weights of all the boarding seats of the cabin;
the sixth determination unit 36 determines a boarding probability for a cabin based on the scattered passenger boarding weights, the team boarding weights, and the total boarding weights for the cabin.
Cabin sections represent divisions of a flight shelter, such as: the flight has two levels of cabin, namely a official cabin and an economic cabin, and the cabin sections are divided into two corresponding cabin sections, namely the official cabin section and the economic cabin section. The bay section contains different sub-bays, and the flight sales are priced by the bays. The public service cabin comprises a cabin position which can be formed by: the economy cabin comprises a Y cabin, a B cabin, an M cabin and an H cabin, the different cabins also correspond to different prices, and the cabin section is the total set of all cabins.
The boarding probabilities for each of the bunkers can be determined based on the flight seat sales data so that calculation of the boarding probabilities for the bunkers can be achieved based on the boarding rate for each of the bunkers.
The flight seat sales data comprises team data and loose-subscriber data, namely, the seats sold by the flights can have team tickets and loose-subscriber tickets, and when the boarding rate of the cabin is calculated, all the tickets can be calculated uniformly, namely, whether the team tickets or the loose-subscriber tickets are purchased is not distinguished; the team ticket purchase and the loose customer ticket purchase can be calculated respectively. The unified calculation of all the tickets is different from the two calculation modes of distinguishing the team ticket purchase from the bulk ticket purchase.
If team data in the flight seat sales data are processed separately, namely, the team ticket purchase is distinguished from the loose passenger ticket purchase, and the team ticket purchase is calculated respectively, whether the cabin section marketable seat number is the same as the allocated seat number needs to be determined first.
If the number of marketable seats of the bay is the same as the number of allocated seats, it is indicated that all allocated seats in the bay have been marketable, and at this time, it may be determined that the total boarding weight of the bay and the scattered boarding weight of the bay are the same as the team boarding weight of the bay, and the first preset value may be 0.
In this case, the boarding ratio of the cabin is 100, and the standard deviation of the boarding ratio of the cabin is 0.
If the number of marketable seats of the bay is different from the number of allocated seats, it is indicated that all allocated seats in the bay are partially not marketable, and at this time, a first total boarding weight for the bay in the first preset mode needs to be determined based on the number of seat allocation.
The first preset mode may be: a split processing mode. The separation processing mode is a seat allocation mode after the optimization processing by an optimization center of the system.
The seats in this seat allocation mode can only allocate their own class and cannot mix. Such as: the protection number of the 8-fold bunk is 10, after the 7-fold bunk is sold, only the seat of the 8-fold bunk can be sold, and the seat in the 8-fold bunk cannot be sold in a 7-fold seat standard by virtue of the seat in the 8-fold bunk. The protection number of the bunkers refers to seats which are fixedly distributed by each bunk and do not allow other bunkers to borrow and sell.
The seat allocation number is the protection number of the cabin by an EMSR A method in a separation processing mode.
EMSR a is a computational model that expects maximization of marginal seat benefit, comprising: only the separate process model to the own class is protected, and the nested process model across classes can be performed.
Determining a first total boarding weight of the cabin class in a first preset mode based on the seat allocation number, wherein the first total boarding weight is specifically as follows: the difference between the marketable seat number of the cabin segment and the total empty seat allocation number of the cabin segment is determined, and the quotient between the seat allocation number and the difference is determined as the total boarding weight of the cabin segment.
Namely: total boarding weight for bay = number of seat assignments/(number of marketable seats for bay-total number of empty seats for bay).
The team boarding weight of the cabin class is determined, the determination can be performed based on the current final booking number of the team in the cabin class, specifically, the difference between the saleable seat number of the cabin class and the total empty seat allocation number of the cabin class is determined, and the quotient between the current final booking number of the team and the difference is determined as the team boarding weight.
In addition, it may be:
team boarding weight = Min (first total boarding weight for the bay level, the current final booking number of the team/(bay marketable seat number-bay total empty seat allocation number)).
That is, the minimum value between the first total boarding weight of the cabin space and the current final booking number of the team/(the cabin marketable seat number-the cabin total empty seat allocation number) is determined as the team boarding weight.
The scattered passenger boarding weight of the cabin class, namely the difference between the first total boarding weight of the cabin class and the team boarding weight, is determined based on the determined first total boarding weight and team boarding weight.
Since a bay is made up of a plurality of bays in the bay, the total boarding weight of the bay is equal to the sum of the total boarding weights of all bays in the bay.
Namely: total boarding weight of bay = Σtotal boarding weight of bay.
The boarding probability of the cabin is related to the boarding weight of the scattered passengers, the boarding weight of the team and the total boarding weight of the cabin, and the boarding rate of the cabin can be obtained by carrying out weighted summation on the boarding weight of the scattered passengers and the boarding weight of the team of each cabin in the cabin and then carrying out averaging. Thus, determining the cabin node probability may be accomplished according to the following:
determining the product of the boarding weight of the visitor and the boarding probability of the visitor as a first value, and determining the product of the boarding weight of the team and the boarding probability of the team as a second value; and determining the ratio of the sum of the first value and the second value to the total boarding weight of the cabin section as the boarding probability of the cabin section.
Further, the cabin check boarding ratio standard deviation may be calculated simultaneously with the cabin check boarding ratio calculation.
And determining the standard deviation of the boarding rate of the cabin section based on the scattered boarding weight and the team boarding weight of the cabin section.
Specifically, cabin check boarding ratio standard deviation= (boarding weight of loose passenger x boarding ratio standard deviation = (sigma)) 2 ++ (Bolus)Team boarding weight x team boarding rate standard deviation 2 ]﹜ 1/2 。
In addition, it may further include:
after the check boarding rate is determined, determining whether the check boarding rate is smaller than a first preset value, and if the check boarding rate is smaller than the first preset value, adjusting the check boarding rate so that the adjusted check boarding rate reaches the first preset value.
Specifically, the first preset value may be 50%.
Further, the embodiment further includes: a seventh determination unit configured to:
when team data in the flight seat sales data is not processed independently, determining a second total boarding weight for the cabin seats in the first preset mode based on the seat allocation number and the cabin marketable seat number and the allocated seat number; and determining that the team boarding weight of the cabin berth is 0, and simultaneously determining the second total boarding weight of the cabin berth as the scattered passenger total boarding weight of the cabin berth.
If team data in the flight seat sales data are not processed independently, all data in the flight seat sales data are processed according to the loose passenger, at the moment, no team boarding weight exists, the team boarding weight can be directly determined to be 0, and correspondingly, when the team boarding weight is 0, the loose passenger boarding weight is the second total boarding weight of the cabin.
The second total boarding weight for the cabin class may be determined by determining the second total boarding weight for the cabin class in the first preset mode based on the number of seat assignments and the number of cabin class marketable seats and the number of assigned seats.
Determining a second total boarding weight of the cabin class in the first preset mode based on the number of seat allocation, wherein the second total boarding weight is specifically as follows: the difference between the marketable seat number of the cabin segment and the total empty seat allocation number of the cabin segment is determined, and the quotient between the seat allocation number and the difference is determined as the total boarding weight of the cabin segment.
Namely: total boarding weight for bay = number of seat assignments/(number of marketable seats for bay-total number of empty seats for bay).
Wherein the second total boarding weight for determining the cabin class is the same as the first total boarding weight for determining the cabin class, but is determined under different preconditions.
After the second total boarding weight and the first total boarding weight are determined, the team boarding weight and the scattered boarding weight under different conditions are respectively determined, and then the cabin boarding probability is determined based on the same steps.
Further, the cabin check boarding rate calculation system disclosed in the embodiment may be further used for:
when team data in the flight seat sales data are not processed independently, determining a second total boarding weight of the cabin class in a second preset mode based on the current cabin class limiting requirement and the current cabin class limiting requirement; and determining that the team boarding weight of the cabin berth is 0, and simultaneously determining the second total boarding weight of the cabin berth as the scattered passenger total boarding weight of the cabin berth.
In the case where team data in the flight seat sales data is not processed separately, if the first preset mode is adopted, the processing is performed by adopting the above embodiment, and if the first preset mode is not adopted, but the second preset mode is adopted, the second total boarding weight needs to be determined based on the current cabin class restriction requirement and the current cabin class restriction requirement.
Wherein, the flight seat sales data comprises: current cabin class restriction requirements and current cabin class restriction requirements, specifically:
Second total boarding weight = current cabin class restriction requirement/current cabin class restriction requirement.
I.e. the quotient between the current cabin class restriction requirement and the current cabin class restriction requirement is the second total boarding weight.
After the second total boarding weight of the current cabin is determined, the determination of the total boarding weight of the cabin and the boarding rate of the cabin is continued based on the scheme.
Further, the cabin check boarding rate calculation system disclosed in the embodiment may further include: an eighth determination unit is provided for determining, based on the received data,
the first boarding weight is used for determining the cabin class in the second preset mode based on the current cabin class limiting requirement and the current cabin class limiting requirement in the flight seat sales data when the team data in the flight seat sales data are processed independently.
If the team data in the flight seat sales data is processed separately, if the first preset mode is adopted, the processing is performed by adopting the embodiment, and if the first preset mode is not adopted, but the second preset mode is adopted, the first total boarding weight needs to be determined based on the current cabin class restriction requirement and the current cabin class restriction requirement.
At this time, the first boarding weight is: the quotient between the current cabin class restriction requirement and the current cabin class restriction requirement, i.e. the first total boarding weight = current cabin class restriction requirement/current cabin class restriction requirement.
And under the condition that the team data are processed independently in the second preset mode, determining the team boarding weight of the cabin after determining the first total boarding weight. Specific:
first total boarding weight = Min (total boarding weight restrictive demand, current crew bunk restrictive demand/current bunk restrictive demand).
After the team boarding weights of the bunkers are determined, the scattered passenger boarding weights of the bunkers are continuously determined based on the above embodiments, and the total boarding weights of the bunkers and the boarding rate of the bunkers are further determined.
The boarding rate calculation system for the cabin section disclosed in the embodiment determines the boarding rate of each cabin seat in the cabin section based on the flight seat sales data, if team data in the flight seat sales data are processed independently, determines whether the marketable seat number of the cabin section is the same as the allocated seat number, if not, determines the first total boarding weight of the cabin section cabin seat in the first preset mode based on the seat allocation number, determines the team boarding weight of the cabin section cabin seat based on the first total boarding weight of the cabin section cabin seat, determines the loose passenger boarding weight of the cabin section cabin seat based on the first total boarding weight of the cabin section cabin seat and the team boarding weight, and determines the total boarding rate of the cabin section based on the loose passenger boarding weight, the team boarding weight and the total boarding weight of the cabin section. According to the method, the boarding rate of each cabin is determined through the flight seat sales data, and when team data are processed independently, the first total boarding weight, the team boarding weight and the scattered passenger boarding weight of the cabin are determined, so that the boarding rate of the cabin is determined, the boarding rate of flights is determined, and the flight sales condition or the income condition can be determined or adjusted based on the boarding rate, so that the income rate of airlines is improved.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. A cabin check boarding rate calculation method, characterized by comprising:
determining a boarding rate for each of the bays based on the flight seat sales data;
if team data in the flight seat sales data are processed independently, determining whether the cabin section marketable seat number is the same as the allocated seat number;
if the number of the marketable seats of the cabin section is different from the allocated seats, determining a first total boarding weight of the cabin section seats in a first preset mode based on the seat allocation number, specifically: determining a difference between the marketable seat number of the cabin section and the total empty seat allocation number of the cabin section, and determining a quotient between the seat allocation number and the difference as a first total boarding weight of the cabin section; the first preset mode is a separation processing mode, the separation processing mode is a seat distribution mode processed by an optimization center of the system, the seat distribution number is a protection number of the seats obtained by a calculation model for expected seat income maximization in the separation processing mode, and the protection number of the seats refers to seats which are fixedly distributed by each seat and do not allow other seats to borrow for sale;
Determining a team boarding weight of the cabin class based on the first total boarding weight of the cabin class, specifically determining the minimum value of the first total boarding weight of the cabin class and the current final booking number of the team/(cabin marketable seat number-cabin class total empty seat allocation number) as the team boarding weight;
determining the scattered passenger boarding weight of the cabin class based on the first total boarding weight and the team boarding weight of the cabin class, and determining the total boarding weight of the cabin class based on the first total boarding weights of all cabin class classes in the cabin class;
determining the boarding rate of the cabin node based on the boarding weight of the scattered passengers, the boarding weight of the team and the total boarding weight of the cabin node, and specifically: determining the product of the boarding weight of the visitor and the boarding probability of the visitor as a first value, and determining the product of the boarding weight of the team and the boarding probability of the team as a second value; and determining the ratio of the sum of the first value and the second value to the total boarding weight of the cabin section as the boarding rate of the cabin section.
2. The method as recited in claim 1, further comprising:
if team data in the flight seat sales data are not processed independently, determining a second total boarding weight of the cabin seats in a first preset mode based on the seat allocation number and the cabin marketable seats and the allocated seats;
And determining that the team boarding weight of the cabin berth is 0, and simultaneously determining the second total boarding weight of the cabin berth as the scattered passenger total boarding weight of the cabin berth.
3. The method as recited in claim 1, further comprising:
and if team data in the flight seat sales data are processed independently, determining a first total boarding weight of the cabin class in a second preset mode based on the current cabin class limiting requirement and the current cabin class limiting requirement in the flight seat sales data.
4. The method as recited in claim 1, further comprising:
if team data in the flight seat sales data are not processed independently, determining a second total boarding weight of the cabin class in a second preset mode based on the current cabin class limiting requirement and the current cabin class limiting requirement;
and determining that the team boarding weight of the cabin berth is 0, and simultaneously determining the second total boarding weight of the cabin berth as the scattered passenger total boarding weight of the cabin berth.
5. The method as recited in claim 1, further comprising:
determining whether the cabin check boarding rate is less than a first preset value;
And if the cabin check boarding rate is smaller than the first preset value, adjusting the cabin check boarding rate.
6. The method as recited in claim 1, further comprising:
and determining the standard deviation of the boarding rate of the cabin section based on the scattered boarding weight and the team boarding weight of the cabin section.
7. A cabin check boarding ratio calculation system, comprising:
a first determination unit for determining a boarding rate of each of the bays based on the flight seat sales data;
a second determining unit for determining whether the cabin section marketable seat number is the same as the allocated seat number when team data in the flight seat sales data are processed separately;
a third determining unit, configured to determine, when it is determined that the number of marketable seats of the cabin segment is different from the number of allocated seats, a first total boarding weight for the cabin segment in the first preset mode based on the number of seat allocation, specifically: determining a difference between the marketable seat number of the cabin section and the total empty seat allocation number of the cabin section, and determining a quotient between the seat allocation number and the difference as a first total boarding weight of the cabin section; the first preset mode is a separation processing mode, the separation processing mode is a seat distribution mode processed by an optimization center of the system, the seat distribution number is a protection number of the seats obtained by a calculation model for expected seat income maximization in the separation processing mode, and the protection number of the seats refers to seats which are fixedly distributed by each seat and do not allow other seats to borrow for sale;
A fourth determining unit, configured to determine a team boarding weight of the cabin space based on the first total boarding weight of the cabin space, specifically determine a minimum value of the first total boarding weight of the cabin space and a current final booking number/(cabin marketable seat number-cabin total empty seat allocation number) of a team as the team boarding weight;
a fifth determining unit, configured to determine a loose boarding weight of the cabin space based on the first total boarding weights of all the cabin spaces in the cabin space and the team boarding weights, and determine the total boarding weight of the cabin space based on the first total boarding weights of all the cabin spaces in the cabin;
a sixth determining unit, configured to determine the boarding rate of the cabin section based on the boarding weight of the loose passenger, the boarding weight of the team, and the total boarding weight of the cabin section, specifically: determining the product of the boarding weight of the visitor and the boarding probability of the visitor as a first value, and determining the product of the boarding weight of the team and the boarding probability of the team as a second value; and determining the ratio of the sum of the first value and the second value to the total boarding weight of the cabin section as the boarding rate of the cabin section.
8. The system of claim 7, further comprising:
A seventh determining unit configured to determine, when team data in the flight seat sales data is not processed separately, a second total boarding weight for the cabin class in a first preset mode based on a seat allocation number and a cabin marketable seat number and an allocated seat number; and determining that the team boarding weight of the cabin berth is 0, and simultaneously determining the second total boarding weight of the cabin berth as the scattered passenger total boarding weight of the cabin berth.
9. The system of claim 7, further comprising:
and an eighth determining unit, configured to determine, when team data in the flight seat sales data is processed separately, a first total boarding weight of the cabin class in the second preset mode based on the current cabin class restriction requirement and the current cabin class restriction requirement in the flight seat sales data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011372647.9A CN112396247B (en) | 2020-11-30 | 2020-11-30 | Cabin check boarding rate calculation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011372647.9A CN112396247B (en) | 2020-11-30 | 2020-11-30 | Cabin check boarding rate calculation method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112396247A CN112396247A (en) | 2021-02-23 |
| CN112396247B true CN112396247B (en) | 2024-03-05 |
Family
ID=74605605
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011372647.9A Active CN112396247B (en) | 2020-11-30 | 2020-11-30 | Cabin check boarding rate calculation method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112396247B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5241142A (en) * | 1988-06-21 | 1993-08-31 | Otis Elevator Company | "Artificial intelligence", based learning system predicting "peak-period" ti |
| CN108475382A (en) * | 2015-12-23 | 2018-08-31 | 瑞士再保险有限公司 | Flight trajectory predictions system and flight track carrying automation risk of time delay transfer system and its corresponding method |
| CN110334959A (en) * | 2019-07-10 | 2019-10-15 | 中国民航信息网络股份有限公司 | A kind of flight freight space resource allocation methods and device |
| CN111784157A (en) * | 2020-06-30 | 2020-10-16 | 中国民航信息网络股份有限公司 | Method and device for allocating boarding gate resources |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130132128A1 (en) * | 2011-11-17 | 2013-05-23 | Us Airways, Inc. | Overbooking, forecasting and optimization methods and systems |
| US10185920B2 (en) * | 2015-02-26 | 2019-01-22 | United Airlines, Inc. | Method and system for automating passenger seat assignment procedures |
-
2020
- 2020-11-30 CN CN202011372647.9A patent/CN112396247B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5241142A (en) * | 1988-06-21 | 1993-08-31 | Otis Elevator Company | "Artificial intelligence", based learning system predicting "peak-period" ti |
| CN108475382A (en) * | 2015-12-23 | 2018-08-31 | 瑞士再保险有限公司 | Flight trajectory predictions system and flight track carrying automation risk of time delay transfer system and its corresponding method |
| CN110334959A (en) * | 2019-07-10 | 2019-10-15 | 中国民航信息网络股份有限公司 | A kind of flight freight space resource allocation methods and device |
| CN111784157A (en) * | 2020-06-30 | 2020-10-16 | 中国民航信息网络股份有限公司 | Method and device for allocating boarding gate resources |
Non-Patent Citations (3)
| Title |
|---|
| 吴光年 等.航空公司超员订票的分析.广东教育学院学报.2006,第26卷(第05期),第48-51页. * |
| 徐丽萍 等.基于超订的民航收益管理单航段舱位控制模型比较研究.系统工程理论与实践.2014,第34卷(第01期),第129-137页. * |
| 李金林 等.超订下网络舱位控制的稳健联合模型及策略.北京理工大学学报.2013,第33卷(第04期),第429-435页. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112396247A (en) | 2021-02-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110334959B (en) | Flight space resource allocation method and device | |
| Nyquist et al. | A study of the airline boarding problem | |
| US8117055B2 (en) | Air cargo yield management system for utilizing booking profiles and unconstrained demand | |
| Tzougas et al. | Optimal bonus-malus systems using finite mixture models | |
| CN111353094A (en) | Information pushing method and device | |
| US20140136247A1 (en) | Use of group materialization rate to release inventory space | |
| CN111539778B (en) | Dynamic pricing method and system for directional pushing | |
| Noronha et al. | Financial health and airline safety | |
| CN114298745A (en) | Data processing method and device, electronic equipment and computer storage medium | |
| CN115345347A (en) | Traffic risk prediction method, device, computer equipment and storage medium | |
| CN109636282B (en) | Air cargo mail distribution method | |
| US20150025920A1 (en) | Check-in reduced carry on baggage system and other boarding process enhancements | |
| CN110956498A (en) | Method and device for evaluating train ticket market supply efficiency | |
| CN112396247B (en) | Cabin check boarding rate calculation method and system | |
| US7487103B2 (en) | System and method for accepting a reservation based on statistical profitability | |
| Thomas et al. | Econometric evidence on the profits and revenues of Indian regional airports | |
| Park et al. | Seat inventory control for sequential multiple flights with customer choice behavior | |
| US20130304524A1 (en) | System and method for jointly optimizing pricing and seat allocation | |
| CN112634062B (en) | Hadoop-based data processing method, device, equipment and storage medium | |
| Lee | Endogenous product characteristics in merger simulation: A study of the us airline industry | |
| Bhatta | Pay-as-you-weigh pricing of an air ticket | |
| US20200311567A1 (en) | Adaptive seat configuration determination system and method | |
| US20060102785A1 (en) | Airplane seating arrangement | |
| Adler et al. | Aiding airlines for the benefit of whom? An applied game-theoretic approach | |
| CN111475702B (en) | Method, system, equipment and medium for warning air-route price based on crawler technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |