煤气与热力2025，Vol.45Issue(1)：12-16,5.
PSO-LSTM模型供水温度预测效果影响分析
Analysis of Influence of Prediction Effect of PSO-LSTM Model for Water Supply Temperature
摘要
Abstract
The particle swarm optimization algo-rithm(PSO)was used to optimize the parameters of the long short-term memory(LSTM)neural network prediction model,the optimization effect of PSO was e-valuated,and the influence of the number of the train-ing set samples on the prediction effect was analyzed.The optimization of parameters of LSTM prediction model by PSO can effectively improve the prediction effect of the prediction model.More training data should be selected to train the prediction model.关键词
供水温度预测/粒子群优化算法/长短期记忆神经网络Key words
prediction of water supply tempera-ture/particle swarm optimization algorithm/long short-term memory neural network分类
建筑与水利引用本文复制引用
郭晓杰,马文菁,曹姗姗,孙春华,夏国强,李孟涵..PSO-LSTM模型供水温度预测效果影响分析[J].煤气与热力,2025,45(1):12-16,5.基金项目
河北省高等学校科学技术研究项目"基于多元时序数据挖掘的供热系统用能模式识别与诊断研究"(QN2021212) （QN2021212）
