A fuzzy neural network to estimate at completion costs of construction projects

In construction cost management system, normally earned value management (EVM) is applied as an efficient control approach in both status detection and estimation at completion (EAC) cost forecasting. The traditional approaches in EAC predictions normally extend the current situation of a project to...

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Main Authors: Morteza Bagherpour, Mohammad Reza Feylizadeh, Ayad Hendalianpour
Format: Article
Language:English
Published: Growing Science 2012-04-01
Series:International Journal of Industrial Engineering Computations
Subjects:
Online Access:http://www.growingscience.com/ijiec/Vol3/IJIEC_2012_12.pdf
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author Morteza Bagherpour
Mohammad Reza Feylizadeh
Ayad Hendalianpour
author_facet Morteza Bagherpour
Mohammad Reza Feylizadeh
Ayad Hendalianpour
author_sort Morteza Bagherpour
collection DOAJ
description In construction cost management system, normally earned value management (EVM) is applied as an efficient control approach in both status detection and estimation at completion (EAC) cost forecasting. The traditional approaches in EAC predictions normally extend the current situation of a project to the future by employing pervious performance factor. The proposed approach of this paper considers both qualitative and quantitative factors affecting the EAC prediction. The proposed approach of this research not only estimates the completion of the project, but also it can generate accurate forecast for the entire future periods using a fuzzy neural network model. The model is also implemented for a real-world case study and yields encouraging preliminary results.
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spelling doaj.art-a7eb105e88e14a75a647c1e2ed521be72022-12-21T20:14:15ZengGrowing ScienceInternational Journal of Industrial Engineering Computations1923-29261923-29342012-04-0133477484A fuzzy neural network to estimate at completion costs of construction projectsMorteza BagherpourMohammad Reza FeylizadehAyad HendalianpourIn construction cost management system, normally earned value management (EVM) is applied as an efficient control approach in both status detection and estimation at completion (EAC) cost forecasting. The traditional approaches in EAC predictions normally extend the current situation of a project to the future by employing pervious performance factor. The proposed approach of this paper considers both qualitative and quantitative factors affecting the EAC prediction. The proposed approach of this research not only estimates the completion of the project, but also it can generate accurate forecast for the entire future periods using a fuzzy neural network model. The model is also implemented for a real-world case study and yields encouraging preliminary results.http://www.growingscience.com/ijiec/Vol3/IJIEC_2012_12.pdfEACEarned value managementFuzzy neural networkConstruction cost management
spellingShingle Morteza Bagherpour
Mohammad Reza Feylizadeh
Ayad Hendalianpour
A fuzzy neural network to estimate at completion costs of construction projects
International Journal of Industrial Engineering Computations
EAC
Earned value management
Fuzzy neural network
Construction cost management
title A fuzzy neural network to estimate at completion costs of construction projects
title_full A fuzzy neural network to estimate at completion costs of construction projects
title_fullStr A fuzzy neural network to estimate at completion costs of construction projects
title_full_unstemmed A fuzzy neural network to estimate at completion costs of construction projects
title_short A fuzzy neural network to estimate at completion costs of construction projects
title_sort fuzzy neural network to estimate at completion costs of construction projects
topic EAC
Earned value management
Fuzzy neural network
Construction cost management
url http://www.growingscience.com/ijiec/Vol3/IJIEC_2012_12.pdf
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