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Construction project control using artificial neural networks

Published online by Cambridge University Press:  27 February 2009

H. Al-Tabtabai ,
N. Kartam ,
I. Flood  and
A.P. Alex
H. Al-Tabtabai
Affiliation:
Civil Engineering Department, College of Engineering and Petroleum, Kuwait University, P.O. Box 5969, Safat 13060, Kuwait.
N. Kartam
Affiliation:
Civil Engineering Department, College of Engineering and Petroleum, Kuwait University, P.O. Box 5969, Safat 13060, Kuwait.
I. Flood
Affiliation:
ME Rinker Sr. School of Building Construction, Gainesville, Florida 32611, USA
A.P. Alex
Affiliation:
Civil Engineering Department, College of Engineering and Petroleum, Kuwait University, P.O. Box 5969, Safat 13060, Kuwait.
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Abstract

Artificial neural networks are finding wide application to a variety of problems in civil engineering. This paper describes how artificial neural networks can be applied in the area of construction project control. A project control system capable of predicting and monitoring project performance (e.g., cost variance and schedule variance) based on observations made from the project environment is described. This project control system has five neural network modules that allow a project manager to automatically generate revised project plans at regular intervals during the progress of the project. These five modules are similar in design and implementation. Therefore, this paper will present the main issues involved in the development of one of these five neural network modules, that is, the module for identifying schedule variance. A description of a graphical user interface integrating the neural network modules developed with project management software, and a discussion on the power and limitations of the overall system conclude the paper.

Keywords

Construction Project ControlArtificial Neural NetworksSchedule ControlCost Control

Information

Type
Articles
Information
AI EDAM , Volume 11 , Issue 1 , January 1997 , pp. 45 - 57
Copyright
Copyright © Cambridge University Press 1997

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