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TRAFFIC CONGESTION PREDICTION SYSTEM, TRAFFIC CONGESTION PREDICTION METHOD, LEARNING DEVICE, PREDICTION DEVICE, PROGRAM AND LEARNED MODEL

机译:交通拥堵预测系统,交通拥堵预测方法,学习设备,预测设备,程序和学习模型

摘要

To achieve provision of traffic congestion information with high precision.SOLUTION: The traffic congestion prediction system includes: an input section which inputs, as input information, traffic information showing a traffic volume, a speed and a length of a vehicle which has run on a road for each sampling time at each of a plurality of points on the road; a first learning section in which a variable for predicting whether or not traffic congestion occurs within a predetermined time generates a first learned model having subjected to mechanical learning with the traffic information and the information showing whether or not traffic congestion occurs within a predetermined time on a road as teacher data; and a first traffic congestion prediction section which calculates prediction information showing whether or not traffic congestion occurs at a first point of time at which a predetermined time elapses after a reference point of time on a road, on the basis of the variable subjected to mechanical learning in the learned model when the traffic information as information to be predicted is input into the input section.SELECTED DRAWING: Figure 1
机译:为了实现高精度的交通拥堵信息的提供。解决方案:交通拥堵预测系统包括:输入部分,其输入表示在道路上行驶的车辆的交通量,速度和长度的交通信息作为输入信息。在道路上多个点的每个点的每个采样时间的道路;在第一学习部分中,用于预测在预定时间内是否发生交通拥堵的变量生成第一学习模型,该第一学习模型已通过交通信息和表示在预定时间内是否在预定时间内发生交通拥堵的信息进行了机械学习。道路作为教师数据;第一交通拥堵预测部基于机械学习的变量,计算表示在道路上的基准时间点之后经过预定时间的第一时间点是否发生交通拥堵的预测信息。在学习模型中,将交通信息作为要预测的信息输入到输入部分。选定的图:图1

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