智能城市2026，Vol.12Issue(2)：13-16,4.DOI:10.19301/j.cnki.zncs.2026.02.003
基于交通生成的共享单车投放量估计方法研究
Research on estimating the deployment volume of shared bicycles based on traffic generation
摘要
Abstract
To address the issue of uneven distribution of shared bicycles in operations,the article proposes a method for estimating the deployment volume of shared bicycles.It screens and classifies shared bicycle data,summarizes the generation and attraction volumes at different parking stations,and evaluates the supply-demand balance of shared bicycles.Using gray relational analysis and correlation coefficients,it identifies the indicators affecting travel rates,selecting the number of residential units,land area,and building area as input variables to construct a BP neural network travel volume prediction model.By combining residential building travel rates and the travel share rate of shared bicycles,the deployment volume of bicycles is estimated.This method was applied in an empirical study in Hefei,and the results show that the estimation error of deployment volume is 6.48%,with prediction performance better than models such as CNN and PSO-SVM.This method can effectively generate shared bicycle deployment volumes,providing a reference for shared bicycle operation management.关键词
单车投放/出行率/共享单车/需求预测/神经网络Key words
bicycle deployment/trip rate/bike sharing/demand forecasting/neural network分类
交通工程引用本文复制引用
王世广,唐卓佳,郝彤宇,汪颖,何瑾瑜..基于交通生成的共享单车投放量估计方法研究[J].智能城市,2026,12(2):13-16,4.基金项目
安徽省哲学社会科学规划项目(AHSKQ2022D075) （AHSKQ2022D075）
