A spatial data statistical model of urban road traffic accidents

被引：0
|
作者：
Liu D.X. [1 ]
机构：
[1] School of intelligent Transportation, Zhejiang Institute of Communications, Hangzhou
来源：
Advances in Transportation Studies | 2022年 / 2卷 / Special Issue期
关键词：
Accident spatial data; Bayesian network; Correction function; Distribution status; Noisy data; Statistical model;
D O I：
10.53136/97912599491966
中图分类号：
学科分类号：
摘要：
There are many problems in traffic accident data statistics, such as large statistical error, high data noise and long time-consuming. The spatial data statistical model of urban road traffic accident is designed. Firstly, determine the distribution state of traffic accident spatial data, extract the traffic accident spatial data under the uniform distribution state with the help of Bayesian network, and transform the randomly distributed accident spatial data into linear data; Then, the decision tree is used to calculate the information entropy of noisy traffic accident spatial data, determine the proportion of noisy data, and complete the preprocessing; Finally, the objective function is used to optimize the data membership, construct the spatial data statistical model of urban road traffic accidents, and complete the design of the spatial data statistical model. The experimental results show that the statistical data error of the design model is less than 2%. © 2022, Aracne Editrice. All rights reserved.
引用
收藏
页码：57 / 66
页数：9
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