The invention relates to a traffic accident severity prediction method and system based on a recurrent neural network, and the method specifically comprises the following steps: S1, carrying out the discretization of continuous variables in the influence factors of a traffic accident, and obtaining a quantitative index table corresponding to each accident factor; s2, clustering the accident data based on a density clustering algorithm OPTICS, compiling and realizing the algorithm based on a Python environment, and obtaining a training sample set of accident severity; s3, parameters such as a loss function, an activation function and an optimizer of the deep learning model are selected based on Keras, and model training and training result visualization are achieved; and S4, inputting quantitative data corresponding to various influence factors of the real road traffic accident into the trained recurrent neural network, and outputting a prediction result of the severity of the traffic accident. According to the method, the severity of the urban road traffic accident can be effectively predicted, and the safety of urban road operation is improved.

    本发明涉及一种基于循环神经网络的交通事故严重程度预测方法及系统,具体包含以下步骤:S1将交通事故的影响因素中的连续变量进行离散化设置,得到各事故因素对应的量化指标表;S2基于密度聚类算法OPTICS将事故数据进行聚类,基于Python环境编译实现其算法,得到事故严重程度的训练样本集;S3基于Keras选取深度学习模型的损失函数、激活函数、优化器等参数,实现模型的训练以及训练结果可视化;S4将真实道路交通事故各种影响因素对应的量化数据,输入训练后的循环神经网络,输出交通事故严重程度的预测结果。本发明可对城市道路交通事故严重程度进行有效的预测,提高城市道路运行的安全性。


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    Titel :

    Traffic accident severity prediction method based on recurrent neural network


    Weitere Titelangaben:

    基于循环神经网络的交通事故严重程度预测方法


    Beteiligte:
    XU XUECAI (Autor:in) / QIAN CHENG (Autor:in) / XIAO DAIQUAN (Autor:in)

    Erscheinungsdatum :

    2024-02-02


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    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 / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / 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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