This paper proposes an optimized prediction algorithm of radial basis function neural
network based on an improved artificial bee colony (ABC) algorithm in the big data …

The paper explores the potential of Multi-Output Gaussian Processes to tackle network-wide
travel time prediction in an urban area. Forecasting in this context is challenging due to the …

This study proposes a novel Bayesian hierarchical approach for online bus speed prediction
by explicitly accounting for the spatiotemporal interaction (STI) of speed observations. The …

Scholars have long sought to identify key city locations that have a pronounced effect on the
flow of people under various conditions. Identifying key locations makes it possible for …

Providing efficient, sustainable and personalized mobility services in urban environments
that combine a spectrum of transport modes (eg, public transport, electric vehicles, vehicle …

Bus speed modeling is essential for effective operation and management of public transit
systems. Space-time interaction patterns are being ignored when modeling bus speed, and …

The provision of efficient, sustainable, and personalized mobility services that combine a
broad range of transport modes (eg, public transportation, electric vehicles (EVs), vehicle …

准确获取交通流量变化点, 对后续的交通流预测, 分类及多时段控制具有重要意义.
鉴于交通流时间序列的非负性及异方差性, 采用Gamma 分布拟合交通流时间序列 …

Considering the particularity, complexity and uncertainty of influencing factors, a dynamic
estimation model of reservation registration service time based on binary attribute similarity …

Over the past few years, several algorithms have been developed to predict travel time. One
of the most important algorithms is Kalman filter, which has been widely used in estimating …