智能城市2025，Vol.11Issue(3)：41-43,3.DOI:10.19301/j.cnki.zncs.2025.03.012
基于小波神经网络的轨道交通短时客流预测
Short-term passenger flow prediction of urban rail transit based on wavelet neural network
陈通箭 1沈德魁1
作者信息
- 1. 平阳县交通运输局,浙江 温州 325000
- 折叠
摘要
Abstract
In order to further explore the issue of short-term passenger flow prediction for urban rail transit,this paper analyzes the factors influencing the short-term passenger flow of urban rail transit from three aspects and extracts the main influencing factors.Wavelet neural network is used for prediction under two conditions,and the prediction results are evaluated by mean absolute percentage error and root mean square error.The results show that the model has good stability and excellent prediction performance.Regardless of whether the model input variables are in a specific time sequence,the overall prediction error of the model is within 10%.This model is suitable for short-term passenger flow prediction of urban rail transit and can provide a reference for the management and operation of urban rail transit.关键词
城市轨道交通/客流量/短时预测/小波神经网络Key words
urban rail transit/passenger flow/short-term prediction/WNN分类
交通运输引用本文复制引用
陈通箭,沈德魁..基于小波神经网络的轨道交通短时客流预测[J].智能城市,2025,11(3):41-43,3.
