A. McCoy, Dong Zhao, Yunjeong Mo, P. Agee, Frederick Paige
{"title":"多户绿色建筑造价与能效的潜在关系","authors":"A. McCoy, Dong Zhao, Yunjeong Mo, P. Agee, Frederick Paige","doi":"10.1049/PBPO155E_CH8","DOIUrl":null,"url":null,"abstract":"Residential buildings have accounted for more than 20% of total energy usage in the United States over the last decade. Reducing household energy consumption has environmental and economic impacts. Building scientists and construction engineers have attempted to obtain accurate energy use prediction; however, few have focused on the relationship between construction cost and energy use. This chapter investigates the associations among detailed construction cost takeoffs and actual energy use in multifamily green buildings. The researchers employ advanced machine-learning analytics to model the correlations between construction costs and energy use data collected from multifamily residential units. The findings identify cost divisions in the construction stage that significantly correlate with energy use in the operational stage. The model allows developers to predict energy consumption based on construction costs and enables them to adjust their investment strategies to amplify the energy efficiency of green building technologies.","PeriodicalId":443101,"journal":{"name":"Energy Generation and Efficiency Technologies for Green Residential Buildings","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Latent relationships between construction cost and energy efficiency in multifamily green buildings\",\"authors\":\"A. McCoy, Dong Zhao, Yunjeong Mo, P. Agee, Frederick Paige\",\"doi\":\"10.1049/PBPO155E_CH8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Residential buildings have accounted for more than 20% of total energy usage in the United States over the last decade. Reducing household energy consumption has environmental and economic impacts. Building scientists and construction engineers have attempted to obtain accurate energy use prediction; however, few have focused on the relationship between construction cost and energy use. This chapter investigates the associations among detailed construction cost takeoffs and actual energy use in multifamily green buildings. The researchers employ advanced machine-learning analytics to model the correlations between construction costs and energy use data collected from multifamily residential units. The findings identify cost divisions in the construction stage that significantly correlate with energy use in the operational stage. The model allows developers to predict energy consumption based on construction costs and enables them to adjust their investment strategies to amplify the energy efficiency of green building technologies.\",\"PeriodicalId\":443101,\"journal\":{\"name\":\"Energy Generation and Efficiency Technologies for Green Residential Buildings\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Generation and Efficiency Technologies for Green Residential Buildings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/PBPO155E_CH8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Generation and Efficiency Technologies for Green Residential Buildings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/PBPO155E_CH8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Latent relationships between construction cost and energy efficiency in multifamily green buildings
Residential buildings have accounted for more than 20% of total energy usage in the United States over the last decade. Reducing household energy consumption has environmental and economic impacts. Building scientists and construction engineers have attempted to obtain accurate energy use prediction; however, few have focused on the relationship between construction cost and energy use. This chapter investigates the associations among detailed construction cost takeoffs and actual energy use in multifamily green buildings. The researchers employ advanced machine-learning analytics to model the correlations between construction costs and energy use data collected from multifamily residential units. The findings identify cost divisions in the construction stage that significantly correlate with energy use in the operational stage. The model allows developers to predict energy consumption based on construction costs and enables them to adjust their investment strategies to amplify the energy efficiency of green building technologies.