Development of SVM model for reliability analysis of railway system
The aim of the research was to develop and demonstrate the applicability of SVM models to identify abnormal state and indentify the onset of failures in railway infrastructure.
Researcher: Yuan Fuqing, Uday Kumar
This project aims to develop Support Vector Machine (SVM) models to estimate and predict railway system reliability. The SVM method has been found to be more accurate and powerful in identifying the trends and deviations in data sets. During the project, mathematical algorithm is developed to identify deviation from normal operation indicating on coming failures. This method can also help identifying any abnormal operation state thereby providing warning for impending failures. During the research, SVM models will be combined with classical statistical techniques such as Bayesian Inference, ANOVA, etc.