An Improved Hybrid XGBoost Model for Culvert Inspection Using Swarm Intelligence Algorithms-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

An Improved Hybrid XGBoost Model for Culvert Inspection Using Swarm Intelligence Algorithms

Published:2024-01-25 Issue: Volume:62 Page:100-108
ISSN:
Container-title:Computing in Civil Engineering 2023
language:
Short-container-title:

Author:

Mohammadi Pouria¹²³,Rashidi Abbas¹²³,Asgari Sadegh¹²³

Affiliation:

1. Ph.D. Student, Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City, UT. ORCID: .

2. Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City, UT.

3. Associate Professor, Dept. of Civil Engineering, Merrimack College, North Andover, MA.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784485224.013

Reference20 articles.

1. Clustering analysis using a novel locality-informed grey wolf-inspired clustering approach;Aljarah I.;Knowl. Inf. Syst,2020

2. Factors for rating condition of culverts for repair or replacement needs;Cahoon J. E.;Transp. Res. Rec,2002

3. Chen T. and C. Guestrin. 2016. “Xgboost: A scalable tree boosting system.” Proc. 22nd acm sigkdd Int. Conf. Knowl. Discov. data Min. 785–794.

4. Highway asset and pavement condition management using mobile photogrammetry;Farhadmanesh M.;Transp. Res. Rec,2021

5. Fouad M. M. A. I. Hafez A. E. Hassanien and V. Snasel. 2015. “Grey wolves optimizer-based localization approach in WSNs.” 2015 11th Int. Comput. Eng. Conf. 256–260. IEEE.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Improving Culvert Condition Prediction Models Using Federated Learning: The Case Study of Utah;Construction Research Congress 2024;2024-03-18

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3