Predicting the near-future delay with accuracy for trains is momentous railway operations and passengers’ traveling experience. This work aims to design prediction models train delays based on Netherlands Railway data. We first develop a chi-square test show that evolution over stations follows first-order Markov chain. then propose model non-homogeneous chains. To deal sparsity of transition m...

The drawback of indirect multi-step-ahead prediction is error accumulation. In order to tackle this problem and improve the capacity of adaptive time delay neural network (ATNN) for prediction, a three-stage prediction model SATNN based on spline interpolation and ATNN is presented. With spline interpolation and ATNN, the impact of last prediction errors that would be iterated into the model fo...

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 later delay management timetable optimization. First, nine characteristics (e.g., buffer time, the number, station code) associated with are chosen analyzed using extra trees classifier. Next, an ELM one hidden layer deve...

The end-to-end delay is one of the most critical and fundamental issues for wireless sensor networks. Many applications of sensor networks require an end-to-end delay guarantee for time sensitive data. However, the end-to-end delay is difficult to bound for event-driven sensor networks, where nodes generate and propagate data only when an event of interest occurs, thereby producing unpredictabl...

Reciprocity in directed networks points to user’s willingness to return favors in building mutual interactions. High reciprocity has been widely observed in many directed social media networks such as following relations in Twitter and Tumblr. Therefore, reciprocal relations between users are often regarded as a basic mechanism to create stable social ties and play a crucial role in the formati...