{"title":"使用极端梯度提升(XGBoost)机器学习预测建筑成本超支","authors":"G. H. Coffie, S. Cudjoe","doi":"10.1080/15623599.2023.2289754","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":47375,"journal":{"name":"International Journal of Construction Management","volume":"9 3","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2023-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using extreme gradient boosting (XGBoost) machine learning to predict construction cost overruns\",\"authors\":\"G. H. Coffie, S. Cudjoe\",\"doi\":\"10.1080/15623599.2023.2289754\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":47375,\"journal\":{\"name\":\"International Journal of Construction Management\",\"volume\":\"9 3\",\"pages\":\"\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2023-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Construction Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/15623599.2023.2289754\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Construction Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/15623599.2023.2289754","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
期刊介绍:
The International Journal of Construction Management publishes quality papers aiming to advance the knowledge of construction management. The Journal is devoted to the publication of original research including, but not limited to the following: Sustainable Construction (Green building; Carbon emission; Waste management; Energy saving) Construction life cycle management Construction informatics (Building information modelling; Information communication technology; Virtual design and construction) Smart construction (Robotics; Artificial intelligence; 3D printing) Big data for construction Legal issues in construction Public policies for construction Building and Infrastructures Health, safety and well-being in construction Risk management in construction Disaster management and resilience Construction procurement Construction management education