现代信息科技2025，Vol.9Issue(22)：1-6,6.DOI:10.19850/j.cnki.2096-4706.2025.22.001
基于LSTM神经网络的区域共享单车需求分析与预测
Regional Sharing Bicycle Demand Analysis and Prediction Based on LSTM
摘要
Abstract
Sharing bicycles make a certain contribution to alleviating traffic congestion and promoting green mobility,but the uneven allocation of resources in actual operation can lead to the problem of declining service quality.Accurate prediction of demands for sharing bicycles can optimize scheduling strategies and improve operational efficiency and service quality.Therefore,a sharing bicycle demand prediction model is constructed based on LSTM.The data features are mainly extracted by analyzing the environmental and temporal factors,and feature engineering is performed.Then LSTM and RNN models are constructed separately to compare their performance.The experimental results show that the LSTM model outperforms the RNN model in terms of data fitting and exhibits strong prediction performance.The model can effectively assist operators to optimize vehicle scheduling,improve service quality and user satisfaction,and provide a reference basis for efficient management of sharing bicycles.关键词
共享单车/长短期神经网络/特征分析/时序预测Key words
sharing bicycle/LSTM/future analysis/time-series prediction分类
信息技术与安全科学引用本文复制引用
罗晓萱,项中雪,许德衡,王炳琨,余盼..基于LSTM神经网络的区域共享单车需求分析与预测[J].现代信息科技,2025,9(22):1-6,6.基金项目
江西科技学院自然科学项目(ZR2106) （ZR2106）
