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本文主要针对中央空调系统的优化控制进行了相关数据分析。首先进行数据预处理,通过SPSS软件的箱线图分析出异常数据,再将异常数据全部剔除,最后用线性插值法填补缺失值。其次通过主成分分析法分别提取出可控变量和不可控变量的主成分,并进行数据标准化,使数据之间无量纲差异。最后根据线性回归分别建立冷却负载、系统效率、总耗电量和可控变量、不可控变量之间的关系模型。同时,利用残差分析和误差条形图对模型进行可靠性评价。
This text mainly carries on the related data analysis to the central air conditioning system optimization control. First of all, data pretreatment, SPSS software box line graph analysis of abnormal data, and then all the abnormal data removed, and finally the linear interpolation method to fill the missing value. Secondly, the principal components of controllable variables and uncontrollable variables were extracted respectively by principal component analysis, and the data were normalized to make the dimensionless differences between the data. Finally, according to the linear regression to establish the cooling load, the system efficiency, the total power consumption and controllable variables, the relationship between the uncontrollable variables model. At the same time, the reliability of the model was evaluated by using residual analysis and error bar graph.