{"title":"Research on the application of RAGA-PP projection model in sustainable architecture: evaluation and optimization","authors":"Rui Deng","doi":"10.1080/17508975.2023.2256709","DOIUrl":null,"url":null,"abstract":"ABSTRACTThis paper presents an evaluation model for the sustainable development of the construction industry based on the project process model and improved real–coded accelerated genetic algorithm (RAGA–PP model) A comprehensive and representative evaluation index system is established, and the simulation curve conversions are effective with good conversion effect The designed evaluation model can assess the sustainable development of the construction industry both vertically and horizontally and is split into different dimensions for the evaluation process. With comprehensiveness, reliability, representativeness, and objectivity, the proposed model effectively evaluates a regional construction industry's sustainable development and supports its growth direction The results indicate the RAGA–PP model's strong predictive performance and reliability The study also constructs an evaluation system and conducts dimensionless treatment on different indicators, providing valuable insights into understanding and evaluating the sustainable development of the construction industry.KEYWORDS: Accelerated genetic algorithmprojection pursuitsustainableconstructionRAGA-PP projection model Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data that support the findings of this study are available from the corresponding author, upon reasonable request.Additional informationNotes on contributorsRui DengRui Deng obtained her Bachelor's degree in engineering costing from Qingdao University of Technology in 2012. Presently, she is working as a lecturer in the department of building data management, Chongqing Metropolitan College of Science and Technology. Her areas of interest are project management, intelligent construction, building cost and risk management.","PeriodicalId":45828,"journal":{"name":"Intelligent Buildings International","volume":"29 1","pages":"0"},"PeriodicalIF":2.1000,"publicationDate":"2023-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent Buildings International","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/17508975.2023.2256709","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACTThis paper presents an evaluation model for the sustainable development of the construction industry based on the project process model and improved real–coded accelerated genetic algorithm (RAGA–PP model) A comprehensive and representative evaluation index system is established, and the simulation curve conversions are effective with good conversion effect The designed evaluation model can assess the sustainable development of the construction industry both vertically and horizontally and is split into different dimensions for the evaluation process. With comprehensiveness, reliability, representativeness, and objectivity, the proposed model effectively evaluates a regional construction industry's sustainable development and supports its growth direction The results indicate the RAGA–PP model's strong predictive performance and reliability The study also constructs an evaluation system and conducts dimensionless treatment on different indicators, providing valuable insights into understanding and evaluating the sustainable development of the construction industry.KEYWORDS: Accelerated genetic algorithmprojection pursuitsustainableconstructionRAGA-PP projection model Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data that support the findings of this study are available from the corresponding author, upon reasonable request.Additional informationNotes on contributorsRui DengRui Deng obtained her Bachelor's degree in engineering costing from Qingdao University of Technology in 2012. Presently, she is working as a lecturer in the department of building data management, Chongqing Metropolitan College of Science and Technology. Her areas of interest are project management, intelligent construction, building cost and risk management.