Fitting Analysis for Flow Coefficient Predictive Model of Residential Buildings with High Airtightness
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The flow coefficient is an important parameter of air infiltration, affected by many factors, such as building parameters, wind speed and temperature difference between indoor and outdoor. And its modeling is used to adopt the method, multiple linear regression, ignoring the problem caused by characteristic of small sample size. Stepwise regression, least squares and partial least squares (PLSs) with corresponding independent variable screening methods are adopted to obtain the predictive models which are compared with F-test, goodness of fit and CV (RMSE). The result shows that the goodness of fit of apartment’s model and villa’s model received by PLS is increased by 25.9% and 2.2%, respectively, compared with least squares and the PLS models’ CV (RMSE) which are 9.4% and 18.3%. Considering the essential characteristics and fitting results of the three methods, it can be concluded that PLS which is suitable for small sample size is the preferred choice for the establishment of flow coefficient model.
KeywordsAir infiltration Flow coefficient Data fitting
This chapter is supported by the National Key Research and Development Program of China “Near-Zero Energy Building Technology System and Key Technology Development” (number 2017YFC0702600).
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