Fuzzy Inference Model for Railway Track Buckling Prediction
Iwo Słodczyk,
David Fletcher,
Inna Gitman
et al.
Abstract:The application of rail buckling models is often limited by uncertain information with respect to track properties, and many conventional models are poorly suited to network-wide or even regional application. Here, a methodology using fuzzy sets is presented that, when trained using buckling data can use inputs of track properties to predict the minimum buckling temperature increase for a particular track. An investigation of the impact of the size of training data and the influence of key track parameters on … Show more
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