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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
business, management and accounting
Prediction of engineering performance: A neurofuzzy approach
Journal of Construction Engineering and Management, Volume 131, No. 5, Year 2005
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Description
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. ©ASCE.
Authors & Co-Authors
Georgy, Maged E.
Egypt, Cairo
Faculty of Engineering
Chang, Luhmaan
United States, West Lafayette
Lyles School of Civil Engineering
Zhang, Lei
Japan, Tokyo
Bovis Lend Lease Japan
Statistics
Citations: 61
Authors: 3
Affiliations: 3
Identifiers
Doi:
10.1061/(ASCE)0733-9364(2005)131:5(548)
ISSN:
07339364
Study Design
Cross Sectional Study