煤气与热力2024，Vol.44Issue(12)：21-27,7.
基于机器学习的二级管网供水温度预测
Prediction of Water Supply Temperature in Secondary Pipe Network Based on Machine Learning
摘要
Abstract
Taking a heating station in a residen-tial area in Weifang City as the research object,the da-ta such as wind direction,wind speed,weather condi-tions(referring to physical phenomena such as cloudy,sunny,rainy and snowy skies),average outdoor temper-ature,and average indoor temperature were used as in-put variables,prediction models of water supply tem-perature of secondary pipe network based on machine learning were constructed,and the prediction effects of the prediction models were compared.The prediction models include back propagation neural network(BPNN)model,support vector regression(SVR)model,and random forest model.All three prediction models can predict the water supply temperature of the secondary pipe network.Among the three prediction models,the predicted values obtained by the random forest model have a higher degree of agreement with the measured values,and the error fluctuation range be-tween the predicted value and the measured value is smaller.Regardless of weather conditions,the evalua-tion indicators of the random forest model are superior to the other two prediction models.The random forest model has the best prediction performance.Compared with not considering weather conditions,the prediction performance of the random forest model considering weather conditions is improved.关键词
二级管网供水温度/机器学习/预测模型Key words
water supply temperature of second-ary pipe network/machine learning/prediction model分类
建筑与水利引用本文复制引用
张志浩,崔萍,周鑫磊..基于机器学习的二级管网供水温度预测[J].煤气与热力,2024,44(12):21-27,7.基金项目
济南市市校融合发展战略工程项目"可再生能源城乡建设利用"(JNSX2021049) （JNSX2021049）
