[go: up one dir, main page]

Thomas et al., 2022 - Google Patents

Design of software-oriented technician for vehicle's fault system prediction using AdaBoost and random forest classifiers

Thomas et al., 2022

View PDF
Document ID
12800926845506019825
Author
Thomas M
Sumathi S
Publication year
Publication venue
International Journal of Engineering, Science and Technology

External Links

Snippet

Detecting and isolating faults on heavy duty vehicles is very important because it helps maintain high vehicle performance, low emissions, fuel economy, high vehicle safety and ensures repair and service efficiency. These factors are important because they help reduce …
Continue reading at www.ajol.info (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/02—Knowledge representation
    • G06N5/022—Knowledge engineering, knowledge acquisition
    • G06N5/025—Extracting rules from data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386—Retrieval requests
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063—Operations research or analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/04—Inference methods or devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30705—Clustering or classification
    • G06F17/3071—Clustering or classification including class or cluster creation or modification
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computer systems based on specific mathematical models
    • G06N7/005—Probabilistic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6279—Classification techniques relating to the number of classes

Similar Documents

Publication Publication Date Title
US11868101B2 (en) Computer system and method for creating an event prediction model
US12217135B1 (en) Systems and methods for building automotive repair service domain models for processing automotive repair service enterprise data
Sarazin et al. Expert system dedicated to condition-based maintenance based on a knowledge graph approach: Application to an aeronautic system
JP7167009B2 (en) System and method for predicting automobile warranty fraud
US11989667B2 (en) Interpretation of machine leaning results using feature analysis
US20230083255A1 (en) System and method for identifying advanced driver assist systems for vehicles
Vong et al. Simultaneous-fault detection based on qualitative symptom descriptions for automotive engine diagnosis
Yang et al. Learning to recognize actionable static code warnings (is intrinsically easy)
Cankaya et al. Evidence-based managerial decision-making with machine learning: The case of Bayesian inference in aviation incidents
CN114417501A (en) Airborne deployment-oriented health management predictive modeling method
Martínez et al. Rotorcraft virtual sensors via deep regression
Thomas et al. Design of software-oriented technician for vehicle’s fault system prediction using AdaBoost and random forest classifiers
Hennebold et al. Cooperation of Human and Active Learning based AI for Fast and Precise Complaint Management
Omri et al. Machine learning techniques for software quality assurance: A survey
Dhillon et al. Advancing Vehicle Diagnostic: Exploring the Application of Large Language Models in the Automotive Industry
Farea et al. An Explainable AI approach for detecting failures in air pressure systems
Yurek et al. T-PdM: a tripartite predictive maintenance framework using machine learning algorithms
Hussain et al. Predicting and Categorizing Air Pressure System Failures in Scania Trucks using Machine Learning
Li et al. Automatic and interpretable predictive maintenance system
De Freitas et al. Data-Driven Methodology for Predictive Maintenance of Commercial Vehicle Turbochargers
Selvi et al. Fault Prediction for Large Scale Projects Using Deep Learning Techniques
Sahana Software Defect Prediction Based on Classication Rule Mining
Berlin Multi-class Supervised Classification Techniques for High-dimensional Data: Applications to Vehicle Maintenance at Scania
Agrawal et al. Hybrid Deep Ensemble Models for Real-Time Prognostics of Vehicular Engine Health Using Temporal Sensor Data
Suryanarayana Safety of AI Systems for Prognostics and Health Management