Railway operations are vulnerable to delays. Accurate predictions of train arrival and
departure delays improve the passenger service quality and are essential for real-time …

Train dispatching (TD) is at the forefront of all rail operations that transport passengers or
goods. Recent technological advances and the explosion of digital data have introduced …

This paper presents a carefully designed train delay prediction model, called FCLL-Net,
which combines a fully-connected neural network (FCNN) and two long short-term memory …

Temperature rise, associated with global warming, has increased the severity and frequency
of heat waves around the world. Rajasthan and Karnataka are two major states of India and …

Multi-line stations (MLSs) are the intersections of different railway lines; they are crucial for
delay propagation in railway networks. Therefore, the precise prediction of train arrival …

Due to the unsuitable train delay prediction methods currently used in the Netherlands, a
more accurate delay prediction method is needed. In this work, based on the data provided …

As a vital component of train operational control, train delay propagation pattern discovery is
critically important for both railway controllers and passengers. In this study, we present a …

Train delay evolutions exhibit different patterns (ie, increasing delays, decreasing delays, or
unchanged delays), because of the effects of stochastic disturbances and pre-scheduled …

This study aims to propose a hybrid model that comprises support vector regression (SVR)
and a Kalman filter (KF) to improve the train running time prediction accuracy of machine …

In this study, a hybrid method combining extreme learning machine (ELM) and particle
swarm optimization (PSO) is proposed to forecast train arrival delays that can be used for …