Bin Yu

TL;DR: A short-term traffic condition prediction model based on the k-nearest neighbor algorithm that provides a good performance compared with the support vector machine (SVM), artificial neural network (ANN) model, real-time- data model, and history-data model and appears to indicate that the proposed k-NEarest neighbor model is an effective approach in predicting the short- term traffic condition.

TL;DR: The support vector machine model with spatial‐temporal parameters exhibits good performance compared with an artificial neural network, a k‐nearest neighbor model, a historical data‐ based model, and a moving average data‐based model.

TL;DR: The results show that the proposed PSO is an effective method to solve the multi-depot vehicle routing problem, and the carton heterogeneous vehicle routing Problem with a collection depot, and is feasible with a saving of about 28 % in total delivery cost.

TL;DR: The results show that the bi-level model performs well with regard to the objective of reducing travel time costs for all travelers and balancing transit service level among all bus lines.

TL;DR: This study analyzes high-dimensional data from Beijing International Airport and presents a practical flight delay prediction model that enables connected airports to collectively alleviate delay propagation within their network through collaborative efforts.