Statistical model for prediction of railway temperature with an application to controlling thermal buckling

This study developed a statistical model for thermal analysis to describe the variation of railway temperature that aids in detecting the potential excessive displacement in the railway efficiently. In particular, the Seasonal autoregressive integrated moving average (SARIMA) model is adopted to learn and recognize the variation patterns of railroad temperature with time.