Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid Algorithm
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...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2018/3093596 |
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| _version_ | 1849305986804744192 |
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| author | Qichun Bing Dayi Qu Xiufeng Chen Fuquan Pan Jinli Wei |
| author_facet | Qichun Bing Dayi Qu Xiufeng Chen Fuquan Pan Jinli Wei |
| author_sort | Qichun Bing |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-340f0e98f3df4295b56b9e0897bf72d2 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-340f0e98f3df4295b56b9e0897bf72d22025-08-20T03:55:15ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2018-01-01201810.1155/2018/30935963093596Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid AlgorithmQichun Bing0Dayi Qu1Xiufeng Chen2Fuquan Pan3Jinli Wei4College of Automobile and Transportation, Qingdao University of Technology, Qingdao 266520, ChinaCollege of Automobile and Transportation, Qingdao University of Technology, Qingdao 266520, ChinaCollege of Automobile and Transportation, Qingdao University of Technology, Qingdao 266520, ChinaCollege of Automobile and Transportation, Qingdao University of Technology, Qingdao 266520, ChinaCollege of Automobile and Transportation, Qingdao University of Technology, Qingdao 266520, ChinaShort-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.http://dx.doi.org/10.1155/2018/3093596 |
| spellingShingle | Qichun Bing Dayi Qu Xiufeng Chen Fuquan Pan Jinli Wei Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid Algorithm Discrete Dynamics in Nature and Society |
| title | Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid Algorithm |
| title_full | Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid Algorithm |
| title_fullStr | Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid Algorithm |
| title_full_unstemmed | Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid Algorithm |
| title_short | Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid Algorithm |
| title_sort | short term traffic flow forecasting method based on lssvm model optimized by ga pso hybrid algorithm |
| url | http://dx.doi.org/10.1155/2018/3093596 |
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