检索结果-南通市图书馆

A Combination Prediction Model for Short Term Travel Demand of Urban Taxi

Computers, Materials & Continua 2024年第6期79卷 3877-3896页

作者： Mingyuan Li Yuanli Gu Qingqiao Geng Hongru Yu School of Traffic and Transportation Beijing Jiaotong UniversityBeijing100044China Transport Planning and Research Institute Ministry of TransportBeijing100028China

This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing *** model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(ceemdan)and Convolutional Long Short Term Memory Neural Network(convlstm)to predict short-term taxi travel *** ceemdan decomposition method effectively decomposes time series data into a set of modal components,capturing sequence characteristics at different time scales and *** on the sample entropy value of components,secondary processing of more complex sequence components after decomposition is employed to reduce the cumulative prediction error of component sequences and improve prediction *** this basis,considering the correlation between the spatiotemporal trends of short-term taxi traffic,a convlstm neural network model with Long Short Term Memory(LSTM)time series processing ability and Convolutional Neural Networks(CNN)spatial feature processing ability is constructed to predict the travel demand for urban *** combined prediction model is tested on a taxi travel demand dataset in a certain area of *** results show that the ceemdan-convlstm prediction model outperforms the LSTM,Autoregressive Integrated Moving Average model(ARIMA),CNN,and convlstm benchmark models in terms of Symmetric Mean Absolute Percentage Error(SMAPE),Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and R2 ***,the SMAPE metric exhibits a remarkable decline of 21.03%with the utilization of our proposed *** results confirm that our study provides a highly accurate and valid model for taxi travel demand forecasting.

关键词： Urban transport taxi travel demand prediction ceemdan-convlstm modal components

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：