Learning and critiquing pairwise activity relationships for schedule quality control via deep learning-based natural language processing-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Learning and critiquing pairwise activity relationships for schedule quality control via deep learning-based natural language processing

Published:2022-02 Issue: Volume:134 Page:104036
ISSN:0926-5805
Container-title:Automation in Construction
language:en
Short-container-title:Automation in Construction

Author:

Amer Fouad^ORCID,Hockenmaier Julia^ORCID,Golparvar-Fard Mani^ORCID

Funder

National Science Foundation

Publisher

Elsevier BV

Subject

Building and Construction,Civil and Structural Engineering,Control and Systems Engineering

Reference39 articles.

1. The Construction Productivity Imperative;Changali,2015

2. Practice Standard for Scheduling - Third Edition, Project Management Institute;PMI,2019

3. Defense Contract Management Agency, Earned Value Management System (EVMS) Program Analysis Pamphlet (PAP);DefenseContractManagementAgency,2012

4. Schedule Assessment Guide: Best Practices for project schedules;Government Accountability Office,2015

5. National Defense Industrial Association, Planning & Scheduling Excellence Guide (PASEG);NationalDefenseIndustrialAssociation,2019

Cited by 12 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. Smart Techniques Promoting Sustainability in Construction Engineering and Management;Engineering;2024-09

2. DfMA Integrated Assessment Model for Selecting Optimal Design Alternatives in OSC Projects;Buildings;2024-06-08

3. Moving toward lean construction through automation of planning and control in last planner system: A systematic literature review;Developments in the Built Environment;2024-04

4. Text mining and natural language processing in construction;Automation in Construction;2024-02

5. Schedule-Driven Analytics of 3D Point Clouds for Automated Construction Progress Monitoring;Computing in Civil Engineering 2023;2024-01-25

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