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P.F. Kaming*, S.O. Ogunlana#, W. Vidogah** and P.O. Olomolaiye**

*University of Atma Jaya Yogyakarta, Yogyakarta, Indonesia
#Asian Institute of Technology, Bankok, Thailand
**University of Wolverhampton, Wolverhampton, UK

doi:10.4203/ccp.35.4.2

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P.F. Kaming, S.O. Ogunlana, W. Vidogah, P.O. Olomolaiye, "A Prototype KBS for Improving On-Site Productivity in High-Rise Construction", in B.H.V. Topping, (Editor), "Developments in Artificial Intelligence for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 51-60, 1995. doi:10.4203/ccp.35.4.2

Abstract

Site productivity is a major area of concern to construction firms. In this study, some relevant models of site productivity have been reviewed, and a new computer-based model is introduced to aid the monitoring and improvement of site productivity in high-rise construction. IMPROVE II, a knowledge-based system (KBS) for. improving site productivity has been developed using the expert system shell EXSYS. Knowledge was acquired from industry experts, and relevant literature or1 productivity improvement. The knowledge representation uses structured production system, and inference mechanism utilizing backward chaining strategy. Multiple attribute utility theory (MAUT) was adopted for weighting the importance of the factors in developing the knowledge-based system. The system comprises four modules: Method and Technology, Site Management, Working Environment, and Motivation which can diagnose the site productivity problems separately.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 35 DEVELOPMENTS IN ARTIFICIAL INTELLIGENCE FOR CIVIL AND STRUCTURAL ENGINEERING Edited by: B.H.V. Topping Paper IV.2 A Prototype KBS for Improving On-Site Productivity in High-Rise Construction P.F. Kaming, S.O. Ogunlana#, W. Vidogah* and P.O. Olomolaiye** University of Atma Jaya Yogyakarta, Yogyakarta, Indonesia #Asian Institute of Technology, Bankok, Thailand *University of Wolverhampton, Wolverhampton, UK doi:10.4203/ccp.35.4.2 purchase the full-text of this paper Full Bibliographic Reference for this paper P.F. Kaming, S.O. Ogunlana, W. Vidogah, P.O. Olomolaiye, "A Prototype KBS for Improving On-Site Productivity in High-Rise Construction", in B.H.V. Topping, (Editor), "Developments in Artificial Intelligence for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 51-60, 1995. doi:10.4203/ccp.35.4.2 Abstract Site productivity is a major area of concern to construction firms. In this study, some relevant models of site productivity have been reviewed, and a new computer-based model is introduced to aid the monitoring and improvement of site productivity in high-rise construction. IMPROVE II, a knowledge-based system (KBS) for. improving site productivity has been developed using the expert system shell EXSYS. Knowledge was acquired from industry experts, and relevant literature or1 productivity improvement. The knowledge representation uses structured production system, and inference mechanism utilizing backward chaining strategy. Multiple attribute utility theory (MAUT) was adopted for weighting the importance of the factors in developing the knowledge-based system. The system comprises four modules: Method and Technology, Site Management, Working Environment, and Motivation which can diagnose the site productivity problems separately. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £65 +P&P)
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