Accurate train delay prediction is vital for effective railway traffic planning and management
as well as for providing satisfactory passenger service quality. Despite significant advances …

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 …

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 …

External and internal factors can cause disturbances or disruptions in daily train operations,
leading to deviations from official timetables and passenger delays. As a result, efficient train …

Based on the Bayesian network (BN) paradigm, we propose a hybrid model to predict the
three main consequences of disruptions and disturbances during train operations, namely …

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 …

Data-driven intelligent technologies are promoting a disruptive digital transformation of
human society. Industrial accident prevention is also amid this change. Although many …

This study is meant to investigate the main driving factors of energy consumption structure
(ECS) in China and construct a hybrid prediction model with higher accuracy. In this paper …