Integration of genetic algorithm and support vector machine to predict rail track degradation

Falamarzi, A, Moridpour, S, Nazem, M and Hesami, R 2018, 'Integration of genetic algorithm and support vector machine to predict rail track degradation', in Proceedings of the 6th International Conference on Tra􀃕c and Logistic Engineering (ICTLE 2018), Bangkok, Thailand, 3-5 August 2018, pp. 1-5.


Document type: Conference Paper
Collection: Conference Papers

Title Integration of genetic algorithm and support vector machine to predict rail track degradation
Author(s) Falamarzi, A
Moridpour, S
Nazem, M
Hesami, R
Year 2018
Conference name ICTLE 2018: Intelligent transportation and industrial logistics
Conference location Bangkok, Thailand
Conference dates 3-5 August 2018
Proceedings title Proceedings of the 6th International Conference on Tra􀃕c and Logistic Engineering (ICTLE 2018)
Publisher MATEC Web of Conferences
Place of publication Bangkok, Thailand
Start page 1
End page 5
Total pages 5
Abstract Gradual deviation in track gauge of tram systems resulted from tram traffic is unavoidable. Tram gauge deviation is considered as an important parameter in poor ride quality and the risk of train derailment. In order to decrease the potential problems associated with excessive gauge deviation, implementation of preventive maintenance activities is inevitable. Preventive maintenance operation is a key factor in development of sustainable rail transport infrastructure. Track degradation prediction modelling is the basic prerequisite for developing efficient preventive maintenance strategies of a tram system. In this study, the data sets of Melbourne tram network is used and straight rail tracks sections are examined. Two model types including plain Support Vector Machine (SVM) and SVM optimised by Genetic Algorithm (GA-SVM) have been applied to the case study data. Two assessment indexes including Mean Squared Error (MSE) and the coefficient of determination (R2) are employed to evaluate the performance of the proposed models. Based on the results, GA-SVM model produces more accurate outcomes than plain SVM model.
Subjects Transport Engineering
Keyword(s) Maintenance
Track degradation
Gauge
Tram
SVM
GA-SVM
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Created: Fri, 14 Dec 2018, 16:06:00 EST by Catalyst Administrator
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