Automated Estimation Approach for Completion Time for Dam Projects

Hamed Golizadeh, Saeed BANIHASHEMI, Aidan Sadeghifam, Christopher Preece

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

An accurate estimation of construction duration for the successful completion of infrastructure projects is as important a task as keeping a project within the stipulated budget and quality. This research aims at developing an automated approach for estimating the duration of construction for dam projects by virtue of artificial neural network (ANN). Through literature searches and expert interviews, variables that critically influence the construction of dam projects were identified. A wide range of data on Iranian dam projects was used to develop seven ANN models. Different datasets were used to achieve the best performance by assessing the RMSE and R2 values as the reliability and validity indicators. Finally, a web-based automated prototype was developed and validated in order for stakeholders to estimate the duration of dam projects based on the ANN method and benefit from better infrastructure project management practices
Original languageEnglish
Pages (from-to)197-209
Number of pages14
JournalInternational Journal of Construction Management
Volume17
Issue number3
Early online date23 Jun 2016
DOIs
Publication statusPublished - 2017
Externally publishedYes

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Dams
Neural networks
Project management
Artificial neural network
Infrastructure projects

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Golizadeh, Hamed ; BANIHASHEMI, Saeed ; Sadeghifam, Aidan ; Preece, Christopher. / Automated Estimation Approach for Completion Time for Dam Projects. In: International Journal of Construction Management. 2017 ; Vol. 17, No. 3. pp. 197-209.
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Automated Estimation Approach for Completion Time for Dam Projects. / Golizadeh, Hamed; BANIHASHEMI, Saeed; Sadeghifam, Aidan; Preece, Christopher.

In: International Journal of Construction Management, Vol. 17, No. 3, 2017, p. 197-209.

Research output: Contribution to journalArticle

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AU - Sadeghifam, Aidan

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