Experimental results with the urban vehicular flow data of Beijing demonstrate the effectiveness of our presented spatio-temporal Bayesian network predictor.

Dec 24, 2017 · Abstract:A novel predictor for traffic flow forecasting, namely spatio-temporal Bayesian network predictor, is proposed.

A novel predictor for traffic flow forecasting, namely spatiotemporal Bayesian network predictor, is proposed. Unlike existing methods, our approach ...

A novel predictor for traffic flow forecasting, namely spatiotemporal Bayesian network predictor, is proposed. Unlike existing methods, our approach ...

A Bayesian optimized spatial-temporal attention long short-term memory neural network is proposed to improve the prediction performance.

Shiliang Sun, Changshui Zhang, Yi Zhang: Traffic Flow Forecasting Using a Spatio-temporal Bayesian Network Predictor. ICANN (2) 2005: 273-278.

Abstract. A novel predictor for traffic flow forecasting, namely spatio- temporal Bayesian network predictor, is proposed. Unlike existing meth-.

Apr 18, 2025 · A trend spatio-temporal adaptive graph convolution network (TSTA-GCN) model for metro passenger flow prediction is presented in this paper.

A novel predictor for traffic flow forecasting, namely spatiotemporal Bayesian network predictor, is proposed. Unlike existing methods, our approach ...

May 14, 2024 · In this paper, we propose a Bayesian Graph Convolutional Network (BGCN) framework to alleviate these issues.