Prediction of Engineering Performance: A Neurofuzzy Approach
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Volume 131, Issue 5
Abstract
Engineering and design professionals constitute a major driving force for a successful project undertaking. Although the industry has been active in addressing the performance of construction labor and methods to estimate or predict such performance, relatively fewer efforts have been conducted for the engineering profession. In an attempt to fill out this gap, the paper presents a study to utilize neurofuzzy intelligent systems for predicting the engineering performance in a construction project. First, neurofuzzy systems are introduced as integrated schemes of artificial neural networks and fuzzy control systems. The use of these neurofuzzy intelligent systems, particularly fuzzy neural networks, in predicting engineering performance is then demonstrated in the industrial construction sector. The development of the system is based on actual project data that was collected through questionnaire surveys. Statistical variable reduction techniques are further employed to develop linear regression models of the same engineering performance prediction scheme, and results are being compared between both techniques.
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Acknowledgments
The writers would like to thank the members of the CII research team on engineering productivity measurement for their help and support throughout the course of this study.
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Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 131 • Issue 5 • May 2005
Pages: 548 - 557
Copyright
© 2005 ASCE.
History
Received: Nov 5, 2002
Accepted: Dec 23, 2004
Published online: May 1, 2005
Published in print: May 2005
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