Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid Algorithm

Qichun Bing, Dayi Qu, Xiufeng Chen, Fuquan Pan and Jinli Wei

Discrete Dynamics in Nature and Society, 2018, vol. 2018, 1-10

Abstract:

Short-term traffic flow forecasting is one of the key issues in the field of dynamic traffic control and management. Because of the uncertainty and nonlinearity, short-term traffic flow forecasting remains a challenging task. In order to improve the accuracy of short-term traffic flow forecasting, a short-term traffic flow forecasting method based on LSSVM model optimized by GA-PSO hybrid algorithm is put forward. Firstly, the LSSVM model is constructed with combined kernel function. Then the GA-PSO hybrid optimization algorithm is designed to optimize the kernel function parameters efficiently and effectively. Finally, case validation is carried out using inductive loop data collected from the north-south viaduct in Shanghai. The experimental results demonstrate that the proposed GA-PSO-LSSVM model is superior to comparative method.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:3093596

DOI: 10.1155/2018/3093596

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