科技创新与应用2025，Vol.15Issue(8)：73-76,4.DOI:10.19981/j.CN23-1581/G3.2025.08.016
基于PSO-SVM的多参数条件下供热负荷预测研究
摘要
Abstract
Heat load is an important parameter in intelligent heating system.Accurate prediction of load demand and accurate regulation are important measures to achieve energy conservation and sustainable operation in intelligent heat supply network.Based on the heat supply data of a heat exchange company in Xinjiang in 2023,this paper selects highly correlated meteorological and parameter characteristics as inputs to build a district heating model based on the PSO-SVM algorithm.Meanwhile,in order to verify the prediction accuracy of the model,The proposed PSO-SVM algorithm is compared with ELM model and BP neural network model prediction method in three evaluation functions.The results show that the prediction accuracy of the constructed PSO-SVM algorithm model is significantly improved.关键词
热负荷预测/PSO-SVM算法/预测精度/智慧供热系统/供热模型Key words
heat load forecasting/PSO-SVM algorithm/forecasting accuracy/intelligent heating system/heating model分类
建筑与水利引用本文复制引用
韩英杰,徐媛媛,胡蓉..基于PSO-SVM的多参数条件下供热负荷预测研究[J].科技创新与应用,2025,15(8):73-76,4.基金项目
第二批自治区产学合作协同育人项目(2023210042,2023210046) （2023210042,2023210046）
中央引导地方科技发展专项资金项目资助(ZYYD2023B19) （ZYYD2023B19）
