基于神经网络模型的智慧城市交通评价系统

IF 0.5 Q4 ENVIRONMENTAL STUDIES INTERNATIONAL JOURNAL OF GLOBAL ENERGY ISSUES Pub Date : 2023-01-01 DOI:10.1504/ijgei.2023.133807
Mingyue Wang
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引用次数: 0

摘要

基于绿色交通与重组的基本内涵和绿色交通的“五位一体”理论,构建了城市绿色交通的评价指标体系,提出了基于BP神经网络的评价模型,并对其进行了验证。本文验证了该方法的效率和合理性,确定了网络层数、传递函数、训练函数、隐藏层神经元的数量,并提供了可行的评估方案,利用MATLAB神经网络工具箱(NNT)设计计算网络,并利用样本训练进行仿真测试。从结果可以看出,城市生态交通BP神经网络评价模型的准确性较高。训练精度可达3.4*10−3量级,输出精度可达10−4量级,模型误差在预定范围内。提出了发展城市生态交通的战略措施。
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Smart city traffic evaluation system based on neural network model
Based on the basic connotation of green transportation and reorganisation and the five-in-one theory of green transportation, the article constructs an evaluation index system for urban green transportation, proposes an evaluation model based on BP neural network, and tests it. The article verifies the efficiency and rationality of this method, determines the number of network layers, transfer function, training function, hidden layer neurons, and provides a feasible evaluation program, uses MATLAB Neural Network Toolbox (NNT) to design the calculation network, and uses sample training for simulation testing. From the results, it can be seen that the accuracy of the urban ecological transportation BP neural network evaluation model is relatively high. The training accuracy can reach 3.4*10−3 magnitude, the output accuracy can reach 10−4 magnitude, and the error of the model is within a predetermined range. The strategic measures for the development of urban ecological transportation are proposed.
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来源期刊
CiteScore
1.50
自引率
0.00%
发文量
58
期刊介绍: IJGEI is a refereed, international journal providing an international forum and authoritative source of information, analyses and discussions on renewable and non-renewable energy resources, energy-economic systems, energy and environment, international energy policy issues, technological innovation and new energy sources. Since the 1970s, attention has been focused on energy resources in the search for sustainable and environmentally non-destructive economic development. The confrontation of ecological limits to growth is not only a technological challenge. Economic, social and natural sciences must be brought together in new perspectives, responding to the concerns expressed worldwide for ecological, social, economic and political dimensions of sustainability.
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