{"title":"探索高效建筑设计中技术因素与舒适度因素之间的关系:对现实世界数据集的统计分析","authors":"Nastaran Deljavan, Hajar Franoudkia","doi":"10.56554/jtom.1332101","DOIUrl":null,"url":null,"abstract":"This study investigates the three factors that contribute to designing efficient buildings, namely technical solutions, facade systems, and occupant requirements, through the use of a real-world dataset consisting of 49 efficient buildings from various locations across the globe. Each factor comprises distinct elements that are essential in achieving building efficiency. Statistical methods, including correlation and Kruskal-Wallis methods, as well as advanced statistical methods such as the reversible jump Markov chain Monte Carlo method, were employed to estimate parameters that represent the conditional dependence between the elements of each factor. The undirected graphs were generated for each factor based on the conditional depence between the elements of the factor which is shown by a link. Through the analysis of these graphs, designers can enhance their comprehension of the correlation between the various elements of each factor, which can ultimately result in improved building efficiency. This, in turn, may lead to a decrease in air pollution and energy consumption while enhancing human comfort.","PeriodicalId":265520,"journal":{"name":"Journal of Turkish Operations Management","volume":" 36","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring the Relationship Between Technical and Comfort Factors in Designing Efficient Buildings: A Statistical Analysis of a Real-World Dataset\",\"authors\":\"Nastaran Deljavan, Hajar Franoudkia\",\"doi\":\"10.56554/jtom.1332101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study investigates the three factors that contribute to designing efficient buildings, namely technical solutions, facade systems, and occupant requirements, through the use of a real-world dataset consisting of 49 efficient buildings from various locations across the globe. Each factor comprises distinct elements that are essential in achieving building efficiency. Statistical methods, including correlation and Kruskal-Wallis methods, as well as advanced statistical methods such as the reversible jump Markov chain Monte Carlo method, were employed to estimate parameters that represent the conditional dependence between the elements of each factor. The undirected graphs were generated for each factor based on the conditional depence between the elements of the factor which is shown by a link. Through the analysis of these graphs, designers can enhance their comprehension of the correlation between the various elements of each factor, which can ultimately result in improved building efficiency. This, in turn, may lead to a decrease in air pollution and energy consumption while enhancing human comfort.\",\"PeriodicalId\":265520,\"journal\":{\"name\":\"Journal of Turkish Operations Management\",\"volume\":\" 36\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Turkish Operations Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.56554/jtom.1332101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Turkish Operations Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56554/jtom.1332101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exploring the Relationship Between Technical and Comfort Factors in Designing Efficient Buildings: A Statistical Analysis of a Real-World Dataset
This study investigates the three factors that contribute to designing efficient buildings, namely technical solutions, facade systems, and occupant requirements, through the use of a real-world dataset consisting of 49 efficient buildings from various locations across the globe. Each factor comprises distinct elements that are essential in achieving building efficiency. Statistical methods, including correlation and Kruskal-Wallis methods, as well as advanced statistical methods such as the reversible jump Markov chain Monte Carlo method, were employed to estimate parameters that represent the conditional dependence between the elements of each factor. The undirected graphs were generated for each factor based on the conditional depence between the elements of the factor which is shown by a link. Through the analysis of these graphs, designers can enhance their comprehension of the correlation between the various elements of each factor, which can ultimately result in improved building efficiency. This, in turn, may lead to a decrease in air pollution and energy consumption while enhancing human comfort.