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Expert System-Based Predictive Cost Model for Building Works: Neural Network Approach

Amusan, L. M. and Mosaku, T. O. and Ayo, C. K. and Adeboye, A. B. (2013) Expert System-Based Predictive Cost Model for Building Works: Neural Network Approach. International Journal of Basic & Applied Sciences IJBAS-IJENS, 13 (01). ISSN 1215804-05-7272

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Abstract

Project managers need accurate estimate of building projects to be able to choose appropriate alternatives for their constructions. Estimated costs of building projects, which hitherto have been based on regression models, are usually left with gaps for high margin of errors and as well, they lack the capacity to accommodate certain intervening variables as construction works progress. Data of past construction projects of the past 2 years were adjusted and used for the study. This model is developed and tested as a predictive cost model for building projects based on Multilayer Perceptron Artificial Neural Networks (ANNs) with Levenberg Marqua. This model is capable of helping professionals save time, make more realistic decisions, and help avoid underestimating and overestimating of project costs. The model is a step ahead of Regression models.

Item Type: Article
Subjects: N Fine Arts > NA Architecture
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Mrs Patricia Nwokealisi
Date Deposited: 30 Jan 2014 14:11
Last Modified: 18 Oct 2017 09:46
URI: http://eprints.covenantuniversity.edu.ng/id/eprint/2104

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