广西师范大学学报（自然科学版）2026，Vol.44Issue(2)：103-114,12.DOI:10.16088/j.issn.1001-6600.2025022101
基于IFA-BP神经网络模型的变电站碳排放预测
Carbon Emission Prediction of Substation Based on IFA-BP Neural Network Model
摘要
Abstract
To solve the problems of existing carbon emission prediction models such as a limited number of indicators and slow data updates,this article proposes a substation carbon emission prediction model based on the improved firefly algorithm(IFA)optimized BP neural network.Firstly,in response to the slow convergence speed and tendency to fall into local optima in the firefly algorithm(FA),teaching and learning factors are introduced to modify the firefly position update process to improve population fitness.Secondly,IFA is introduced to perform hyper-parameter optimization on the BP neural network model,and an IFA-BP neural network prediction model is constructed.Then,based on the CRITIC method,select key carbon emission indicators for the input layer of the prediction model.Finally,the prediction model is trained using the training set data to predict the carbon emissions of the substation based on the trained model.The simulation results show that compared with the three comparison schemes,the root mean square error(RMSE)of the proposed IFA-BP neural network prediction model decreases by 59.61％,15.77％and 26.65％,respectively.The coefficient of determination(R2)increases by 5.66％,1.46％and 1.15％.The feasibility and superiority of the substation carbon emission prediction model proposed in this paper are fully verified.关键词
碳排放/变电站/改进萤火虫算法/BP神经网络/教与学因子Key words
carbon emissions/substation/IFA optimization algorithm/BP neural network/teaching and learning factors分类
资源环境引用本文复制引用
王巍,李智威,张赵阳,张洪,周蠡,王振,黄放,王灿..基于IFA-BP神经网络模型的变电站碳排放预测[J].广西师范大学学报（自然科学版）,2026,44(2):103-114,12.基金项目
国家自然科学基金(52107108) （52107108）
