Prediction model of track quality index based on Genetic algorithm and support vector machine

Abstract

In recent years, the development of modern tram is rapid. In order to guarantee the long-term stable and safe operation of tram, predicting the overall condition of the relevant running lines and guiding the track maintenance are increasingly important. Nevertheless, due to the limitation of data mining and analysis technology, the analysis and application level of modern tramcar track detection data and the prediction level of the overall status of the track are relatively backward in China. Based on the analysis of geometric parameters of original track detection in the section of track quality index (TQI), this paper proposes a set of overall situation prediction model, which is based on the improved vector machine (SVM), and implements the analysis and prediction of TQI change. Meantime this prediction model can provide a new evaluation thought for the overall situation of modern tram track.