Title: Smart city traffic evaluation system based on neural network model

Authors: Mingyue Wang

Addresses: Changchun University of Chinese Medicine, Changchun 130000, Jilin, China

Abstract: 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.

Keywords: urban ecological transport; ecological transport evaluation; index system; neural network model.

DOI: 10.1504/IJGEI.2023.133807

International Journal of Global Energy Issues, 2023 Vol.45 No.6, pp.561 - 585

Received: 25 Dec 2021
Accepted: 27 Sep 2022
Published online: 03 Oct 2023 *

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