The invention relates to a traffic flow prediction method of an SVM (Support Vector Machine) algorithm improved by combining a reverse bat algorithm. According to the method, an improved SVM algorithm combined with a reverse bat algorithm is provided for the problems of uncertainty and randomness of prediction models or parameters, and the novel SVM algorithm has the obvious characteristics that an improved flight principle is developed by adopting a backward flight mechanism, and the random search capability is enhanced, so that local optimum is effectively avoided. Compared with a traditional SVM method, the method has higher training precision, shorter training time and better prediction performance. Therefore, the method can effectively solve the problem of traffic flow prediction.

    本发明涉及一种结合反向蝙蝠算法改进的SVM算法的交通流预测方法。本发明首先针对预测模型或参数的不确定性和随机性的问题,提出了一种结合反向蝙蝠算法改进的SVM算法,新型SVM算法的显着特点是采用后向飞行机制发展了一种改进的飞行原理,增强了随机搜索能力,从而有效地避免了局部最优。与传统的SVM方法相比,它拥有更高的训练精度、更短的训练时间和更好的预测性能。所以此方法可以有效解决交通流预测的问题。


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    Title :

    Traffic flow prediction method based on SVM algorithm improved in combination with reverse bat algorithm


    Additional title:

    一种基于结合反向蝙蝠算法改进的SVM算法的交通流预测方法


    Contributors:
    SUN YUHANG (author) / PEI SHUJUN (author) / REN DINGXIANG (author)

    Publication date :

    2023-02-03


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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