摘要
基于最小二乘法的预测方法,运用线性回归分析整理系统的历史数据,并将天气预报中的室外温度作为自变量,供热负荷作为因变量,同时利用这两个变量的历史数据作为预测样本,对其进行最小二乘法拟合.通过拉依达法判别粗大误差,最终确定线性关系中的回归系数,从而提高供热负荷预测精度.
Based on the prediction method of the least square method,this paper uses the linear regression analysis to sort out the historical data of the system,and takes the outdoor temperature in the weather forecast as the independent variable and the heating load as the dependent variable.At the same time,the historical data of these two variables are used as the prediction samples,which are fitted by the least square method.In order to improve the accuracy of heating load forecasting,the regression coefficient in linear relationship is determined by the method of Pauta criterion.
作者
孟亚男
姚洁
MENG Yanan;YAO Jie(College of Information and Control Engineering,Jilin Institute of Chemical Technology,Jilin City 132022,China)
出处
《吉林化工学院学报》
CAS
2020年第5期31-33,共3页
Journal of Jilin Institute of Chemical Technology
关键词
热负荷预测
室外温度
最小二乘法
heat load forecast
outdoor temperature
least square method