The invention discloses an urban road traffic state prediction system based on deep learning. The prediction is realized by utilizing the following modules: a traffic environment module, a memory bankmodule, a neural network module, a training lifting network module, a visualization module and an interaction module. The traffic environment module comprises an acquisition module and a preprocessing module. The acquisition module acquires urban road position information, peak period average vehicle speed information, air temperature information, rainfall probability information and congestion length information. The preprocessing module performs traffic data preprocessing based on a Lagrange interpolation method and a normalization method to obtain reliable data for traffic prediction, theobtained data are stored in the memory bank module, and a neural network is constructed according to the reliable data so as to construct a deep cyclic learning network of a traffic state.
一种基于深度学习的城市道路交通状态预测系统,利用如下模块实现预测:交通环境模块、记忆库模块、神经网络模块、训练提升网络模块、可视化模块、交互模块;所述交通环境模块包括采集模块、预处理模块,所述采集模块采集城市道路位置信息、高峰期平均车速信息、气温信息、降水概率信息、拥堵长度信息;所述预处理模块基于拉格朗日插值方法与归一化方法进行交通数据预处理,获取用于交通预测的可靠数据,所得数据存入记忆库模块,并根据所述可靠数据构建神经网络,从而构建交通状态的深度循环学习网络。
Urban road traffic state prediction system based on deep learning
一种基于深度学习的城市道路交通状态预测系统
2020-07-10
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / 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 |
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