Predicting the required duration for construction activities using Artificial Neural Networks

The duration of a construction project is a key factor to consider before the project starts, as it can determine the success or failure of the project. Difficulties in estimating the duration of activities that can also lead to error if manually estimate it. The main purpose of this study is to dev...

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Main Author:	Golizadeh, Hamed
Format:	Thesis
Language:	English
Published:	2013
Subjects:	TH Building construction
Online Access:	http://eprints.utm.my/id/eprint/33824/5/HamedGolizadehMFKA2013.pdf
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id	my-utm-ep.33824
record_format	uketd_dc
spelling	my-utm-ep.338242017-09-11T03:40:25Z Predicting the required duration for construction activities using Artificial Neural Networks 2013-01 Golizadeh, Hamed TH Building construction The duration of a construction project is a key factor to consider before the project starts, as it can determine the success or failure of the project. Difficulties in estimating the duration of activities that can also lead to error if manually estimate it. The main purpose of this study is to develop a model to estimate the duration of construction’s major activities in the structural part of concrete frame of buildings. In this study, available methods and models have been investigated and this is achieved through reviewing the previous literatures. It is argued that using Artificial Neural Network (ANN) is the most proper method to achieve the aim of this study. Consequently, through literature investigation and experts interviewing, those factors which can critically influence the activity duration have been opted. Four different buildings in two different regions of Malaysia are selected as case for the project. Finally, the collected data and variables implemented into the models and nine ANN models have been trained, tested and validated. Contractors and firms can utilize these models in the planning phase of their project to avoid the errors made by human beings and producing more accurate estimations of activity durations. 2013-01 Thesis http://eprints.utm.my/id/eprint/33824/ http://eprints.utm.my/id/eprint/33824/5/HamedGolizadehMFKA2013.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:70128?site_name=Restricted Repository masters Universiti Teknologi Malaysia, Faculty of Civil Engineering Faculty of Civil Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TH Building construction
spellingShingle	TH Building construction Golizadeh, Hamed Predicting the required duration for construction activities using Artificial Neural Networks
description	The duration of a construction project is a key factor to consider before the project starts, as it can determine the success or failure of the project. Difficulties in estimating the duration of activities that can also lead to error if manually estimate it. The main purpose of this study is to develop a model to estimate the duration of construction’s major activities in the structural part of concrete frame of buildings. In this study, available methods and models have been investigated and this is achieved through reviewing the previous literatures. It is argued that using Artificial Neural Network (ANN) is the most proper method to achieve the aim of this study. Consequently, through literature investigation and experts interviewing, those factors which can critically influence the activity duration have been opted. Four different buildings in two different regions of Malaysia are selected as case for the project. Finally, the collected data and variables implemented into the models and nine ANN models have been trained, tested and validated. Contractors and firms can utilize these models in the planning phase of their project to avoid the errors made by human beings and producing more accurate estimations of activity durations.
format	Thesis
qualification_level	Master's degree
author	Golizadeh, Hamed
author_facet	Golizadeh, Hamed
author_sort	Golizadeh, Hamed
title	Predicting the required duration for construction activities using Artificial Neural Networks
title_short	Predicting the required duration for construction activities using Artificial Neural Networks
title_full	Predicting the required duration for construction activities using Artificial Neural Networks
title_fullStr	Predicting the required duration for construction activities using Artificial Neural Networks
title_full_unstemmed	Predicting the required duration for construction activities using Artificial Neural Networks
title_sort	predicting the required duration for construction activities using artificial neural networks
granting_institution	Universiti Teknologi Malaysia, Faculty of Civil Engineering
granting_department	Faculty of Civil Engineering
publishDate	2013
url	http://eprints.utm.my/id/eprint/33824/5/HamedGolizadehMFKA2013.pdf
_version_	1747816194126118912

Predicting the required duration for construction activities using Artificial Neural Networks

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