Estimating Construction Project Duration Using a Machine Learning Algorithm

Thesis (M.S.) -- Civil and Environmental Engineering, May 2024

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Nasr, Joshua (author)
التنسيق: masterThesis
منشور في: 2024
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/10725/16096
https://doi.org/10.26756/th.2023.700
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php
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author Nasr, Joshua
author_facet Nasr, Joshua
author_role author
dc.creator.none.fl_str_mv Nasr, Joshua
dc.date.none.fl_str_mv 2024-09-10T10:12:42Z
2024-09-10T10:12:42Z
2024
2024-05-14
dc.identifier.none.fl_str_mv http://hdl.handle.net/10725/16096
https://doi.org/10.26756/th.2023.700
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Lebanese American University
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Construction industry -- Lebanon -- Management
Civil engineering -- Data processing
Machine learning -- Case studies
Lebanese American University -- Dissertations
Dissertations, Academic
dc.title.none.fl_str_mv Estimating Construction Project Duration Using a Machine Learning Algorithm
dc.type.none.fl_str_mv Thesis
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/masterThesis
description Thesis (M.S.) -- Civil and Environmental Engineering, May 2024
eu_rights_str_mv openAccess
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language_invalid_str_mv en
network_acronym_str LAURepo
network_name_str Lebanese American University repository
oai_identifier_str oai:laur.lau.edu.lb:10725/16096
publishDate 2024
publisher.none.fl_str_mv Lebanese American University
repository.mail.fl_str_mv
repository.name.fl_str_mv
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spelling Estimating Construction Project Duration Using a Machine Learning AlgorithmNasr, JoshuaConstruction industry -- Lebanon -- ManagementCivil engineering -- Data processingMachine learning -- Case studiesLebanese American University -- DissertationsDissertations, AcademicThesis (M.S.) -- Civil and Environmental Engineering, May 2024Construction project delays remain one of the most relevant problems in the construction sector. The construction industry is also one of the least digitalized industries. This research aims to use the power of artificial intelligence and machine learning to help better understand the delays faced in building construction projects and be able to estimate them before the project begins. A thorough literature review was conducted to find the main causes of construction delays in Lebanon. A model was then created using the machine learning algorithm extreme gradient boosting (XGBoost) based on factors that quantify the main causes of delay that can be known before the project begins. The goal of the model is to be trained on the training data to accurately predict the delay of projects that were not seen by the model before. Previous research into construction project delays has only created models that classify projects by their delay risk level. No research has been done on the use of machine learning to create regression models that can predict the delay of a project before the project starts. This research fills the gap by creating a model that can estimate construction project delays before projects begin. The model estimated project delays with an error of 24% and an adjusted R² of 74.3%. This shows that the model was able to achieve relatively accurate results and explain 74.3% of the variability of the delay while only using ten factors causing delay. The results show that the factors mostly affecting delay in Lebanese construction projects are the client’s performance, legal issues faced by the project, the project manager’s expertise, and the quality of design documents.1 online resource (x, 59 leaves): ill. (some col.)Includes bibliographical references (leaves 56-59)Lebanese American University2024-09-10T10:12:42Z2024-09-10T10:12:42Z20242024-05-14Thesisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/10725/16096https://doi.org/10.26756/th.2023.700http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.phpeninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/160962024-12-06T13:29:26Z
spellingShingle Estimating Construction Project Duration Using a Machine Learning Algorithm
Nasr, Joshua
Construction industry -- Lebanon -- Management
Civil engineering -- Data processing
Machine learning -- Case studies
Lebanese American University -- Dissertations
Dissertations, Academic
status_str publishedVersion
title Estimating Construction Project Duration Using a Machine Learning Algorithm
title_full Estimating Construction Project Duration Using a Machine Learning Algorithm
title_fullStr Estimating Construction Project Duration Using a Machine Learning Algorithm
title_full_unstemmed Estimating Construction Project Duration Using a Machine Learning Algorithm
title_short Estimating Construction Project Duration Using a Machine Learning Algorithm
title_sort Estimating Construction Project Duration Using a Machine Learning Algorithm
topic Construction industry -- Lebanon -- Management
Civil engineering -- Data processing
Machine learning -- Case studies
Lebanese American University -- Dissertations
Dissertations, Academic
url http://hdl.handle.net/10725/16096
https://doi.org/10.26756/th.2023.700
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php