交通运输研究2016，Vol.2Issue(3)：30-35,6.DOI:10.16503/j.cnki.2095-9931.2016.03.005
基于BP神经网络的公共自行车单站点调度需求量研究
Scheduling Demand of Single Public Bicycle Station Based on BP Neural Network
摘要
Abstract
The scheduling of urban public bicycle rental system plays an essential role in the promotion of public bicycle usage ratio. The key is reasonably predicting the future bicycle usage and ascertaining the scheduling demand of single station. According to the analysis and induction of the historical rent-and-return data and operating characteristic,the frequency of bicycles′rent-and-return in single sta⁃tion was predicted using BP Neural Network model. The average difference between predicted and real values is about 3 units, and the curve fitting is good. It proves the high feasibility of the model. On this basis, the best scheduling demand of single station was confirmed according to the principle of dynamic balance of station saturation in scheduling time window. The case analysis of the central park in Lucheng district, Wenzhou City, Zhejiang Province indicates that implementing the predicted schedule on demand basis could shorten the hours of"no parking space to return"of the single station in the morn⁃ing and evening busy period by more than 0.5h, thereby the service quality and satisfaction degree could be enhanced effectively.关键词
城市公共自行车/车辆调度/预测/需求量/BP神经网络Key words
urban public bicycle/vehicle scheduling/prediction/demand/BP neutral system分类
交通工程引用本文复制引用
陈昕昀,蒋永康,李牧原,柯希玮..基于BP神经网络的公共自行车单站点调度需求量研究[J].交通运输研究,2016,2(3):30-35,6.基金项目
国家大学生创新创业训练计划 （）
