A parallel SVR approach to real-time traffic flow forecasting

作者：Yang Ji Xiang^*; Tan Guo Zhen; Wang Fan; Tian Zhu; Pan Dong

来源：Journal of Dalian University of Technology, 2010, 50(6): 1035-1041.

• Generalized neural network
• Load-Balancing
• Parallel Computing
• Support vector regression (SVR)
• Traffic flow forecasting

Accurate and real-time traffic flow forecasting is a key problem to the application development of intelligent transportation systems (ITS). Comparing with generalized neural network (GNN) method, the theoretical advantage of applying support vector regression (SVR) method to traffic flow forecasting highly depends on good parameter selection. Simple yet practical approach to SVR parameters setting directly from the training set is analyzed and discussed, and a traffic flow SVR forecasting model for large-scale road network and a greedy load balancing (G-LB) algorithm in cluster environment are proposed. Experimental results demonstrate that it can better satisfy real-time and accurate demands of traffic flow forecasting using parallel SVR approach based on G-LB (GLB-SVR) algorithm than using parallel GNN (P-GNN) method.

• 出版日期2010