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dc.contributor.authorNo, Sang-Tae-
dc.contributor.authorSeo, Jun-Sik-
dc.date.accessioned2020-05-29T01:31:48Z-
dc.date.available2020-05-29T01:31:48Z-
dc.date.issued2018-
dc.identifier.issn1687 - 8086-
dc.identifier.otherBBKH1039-
dc.identifier.urihttp://thuvienso.vanlanguni.edu.vn/handle/Vanlang_TV/18400-
dc.description"Hindawi Advances in Civil Engineering Volume 2018, Article ID 1780809, 7 pages https://doi.org/10.1155/2018/1780809"vi
dc.description.abstractCurrently, global warming is accelerating, and many countries are trying to reduce greenhouse emission by enforcing low energy building. And the thermal performance of the windows is one of the factors that greatly influence the heating and cooling energy consumption of buildings. According to the development of the window system, the thermal performance of the windows is greatly improved. There are simulations and tests for window thermal performance evaluation techniques, but both are time consuming and costly. The purpose of this study is to develop a convenient method of predicting U-value at the window system design stage by multiple linear regression analysis. 532 U-value test results were collected, and window system components were set as independent values. As a result, the number of windows (single or double) among the components of the window has the greatest effect on the U-value. In this research, two regression equations for predicting U-value of window system were suggested, and the estimated standard errors of equations were 0.2569 in single window and 0.2039 in double window.vi
dc.language.isoenvi
dc.publisherHindawi Limitedvi
dc.subjectStandardsvi
dc.subjectMathematical analysisvi
dc.subjectPerformance evaluationvi
dc.subjectRegression analysisvi
dc.subjectGreenhouse gasesvi
dc.subjectAir conditioningvi
dc.subjectCalibrationvi
dc.subjectNeural networksvi
dc.subjectCost controlvi
dc.subjectSystems designvi
dc.subjectWindows & doorsvi
dc.titleAnalysis of Window Components Affecting U-Value Using Thermal Transmittance Test Results and Multiple Linear Regression Analysisvi
dc.typeOthervi
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