西安理工大学学报2025，Vol.41Issue(4)：499-508,10.DOI:10.19322/j.cnki.issn.1006-4710.2025.04.005
基于VMD-LSTM的高速公路综合场站碳排放预测研究
Carbon emission prediction of expressway integrated station based on VMD-LSTM
摘要
Abstract
Highway integrated stations are critical nodes for energy consumption and carbon emis-sions in bridge and road construction.To achieve the accurate prediction of its carbon emission,this paper innovatively constructs a carbon emission prediction model combining variational mode decomposition(VMD)and long short-term memory(LSTM)networks,based on 146 days of energy consumption monitoring data from the integrated station of the Changxiu Expressway's Fengqiu to Xiuwu section.The results show that the VMD-LSTM model effectively captures the periodic variation patterns of carbon emissions at the integrated station,with its predicted values trending highly consistent with actual values trends.The model demonstrates excellent a predic-tive performance,achieving an accuracy rate(AR)of 94.32％,mean squared error(MSE)of 0.099 3,root mean squared error(RMSE)of 0.315 0,and coefficient of determination(R2)of 0.973 9,significantly outperforming the traditional LSTM model.The research findings provide the theoretical guidance and technical support for precise energy conservation and carbon reduc-tion in highway integrated stations.关键词
高速公路综合场站/碳排放/变分模态分解/长短期记忆网络/预测模型Key words
expressway integrated station/carbon emission/VMD/LSTM/prediction model分类
资源环境引用本文复制引用
高晓明,许文峰,邱浪,任高峰,郑一柳,么学春,徐琛..基于VMD-LSTM的高速公路综合场站碳排放预测研究[J].西安理工大学学报,2025,41(4):499-508,10.基金项目
中国施工企业管理协会重大科研项目(2023-A-032) （2023-A-032）
