计算机应用研究2017，Vol.34Issue(9)：2692-2695,4.DOI:10.3969/j.issn.1001-3695.2017.09.028
基于网络模型的城市公共自行车需求量预测研究
Research on demand prediction of urban bicycle sharing based on network model
摘要
Abstract
Bicycle-sharing systems are widely deployed in many major cities.As the rents/returns of bicycles at different stations in different periods are unbalanced,the bicycles in a system need to be rebalanced frequently.Real-time monitoring cannot tackle this problem well.Therefore,this paper developed a prediction model based on network diagram to predict the number of bicycles that would be rent from/returned to each station in a future period so that reallocation could be executed in advance.First,it proposed a hierarchical clustering algorithm to cluster bike stations into groups-relevant station clusters.Then,it constructed network model of a relevant station cluster.Finally,it evaluated the model by two bicycle sharing systems in New York City (NYC) and Washington D.C.(D.C.) respectively,compared with the baseline method,historical mean mcthod and ARIMA model.The results manifest that there is a similarity in the same cluster,model prediction error rate is not higher than 0.45.Performance of the network model is better,and can be applied to different urban bicycle sharing systems.关键词
自行车共享系统/分层聚类算法/需求量/预测Key words
bicycle sharing system/hierarchical clustering algorithm/demand number/prediction分类
信息技术与安全科学引用本文复制引用
林燕平,窦万峰..基于网络模型的城市公共自行车需求量预测研究[J].计算机应用研究,2017,34(9):2692-2695,4.基金项目
国家自然科学基金资助项目(41171298) （41171298）
