Research on Substation Engineering Estimates Based on BIM-DE-RF

Pub Date : 2023-01-01 DOI:10.12720/jait.14.5.892-896
Songsong Wang, Wenxuan Qiao, Lei Wang, Zhewei Shen, Pengju Yang, Li Bian
{"title":"Research on Substation Engineering Estimates Based on BIM-DE-RF","authors":"Songsong Wang, Wenxuan Qiao, Lei Wang, Zhewei Shen, Pengju Yang, Li Bian","doi":"10.12720/jait.14.5.892-896","DOIUrl":null,"url":null,"abstract":"—Aiming at the problems of heavy workload and large errors in traditional substation engineering estimation methods, an intelligent estimation method for substation engineering based on Building Information Modeling (BIM) combined with a Differential Evolution (DE) algorithm to optimize Random Forest (RF) is proposed. This proposed method uses DE to optimize the RF model’s splitting features and decision trees to enhance the model’s estimation accuracy. The BIM of the substation project is used to determine engineering quantity information, which serves as the input of the DE-RF model, enabling intelligent cost estimation of the substation project. The results of the example analysis show that the relative error of the proposed cost estimation method for substation engineering based on BIM and DE-RF is below 10%. This accuracy level meets various substation engineering cost estimation scenarios, validating the feasibility and correctness of the proposed model.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12720/jait.14.5.892-896","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

—Aiming at the problems of heavy workload and large errors in traditional substation engineering estimation methods, an intelligent estimation method for substation engineering based on Building Information Modeling (BIM) combined with a Differential Evolution (DE) algorithm to optimize Random Forest (RF) is proposed. This proposed method uses DE to optimize the RF model’s splitting features and decision trees to enhance the model’s estimation accuracy. The BIM of the substation project is used to determine engineering quantity information, which serves as the input of the DE-RF model, enabling intelligent cost estimation of the substation project. The results of the example analysis show that the relative error of the proposed cost estimation method for substation engineering based on BIM and DE-RF is below 10%. This accuracy level meets various substation engineering cost estimation scenarios, validating the feasibility and correctness of the proposed model.
分享
查看原文
基于BIM-DE-RF的变电站工程评估研究
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信