机译:SVRGSA:基于混合学习的短期交通流量预测模型
Shantou Univ Dept Comp Sci Coll Engn Shantou Peoples R China;
South China Univ Technol Sch Comp Sci & Technol Guangdong Prov Key Lab Computat Intelligence & Cy Guangzhou Guangdong Peoples R China;
Shantou Univ Dept Comp Sci Coll Engn Shantou Peoples R China|Hong Kong Polytech Univ Sch Nursing Ctr Smart Hlth Hong Kong Peoples R China;
Hong Kong Polytech Univ Sch Nursing Ctr Smart Hlth Hong Kong Peoples R China;
support vector machines; road traffic; search problems; forecasting theory; learning (artificial intelligence); time series; regression analysis; hybrid learning based model; short-term traffic flow forecasting; efficient forecasting model; robust forecasting model; nonlinear data pattern; time series prediction problems; SVR model; poor forecasting accuracy; hybrid traffic flow forecasting model;
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机译:基于神经网络的基于网络的短期交通流预测使用混合指数平滑和Levenberg-Marquardt算法