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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 35
DEVELOPMENTS IN ARTIFICIAL INTELLIGENCE FOR CIVIL AND STRUCTURAL ENGINEERING
Edited by: B.H.V. Topping
Paper XII.2

CBRefurb: A Case-Based Building Refurbishment Cost Estimator and Decision Support System

F. Marir and I. Watson

Department of Surveying, University of Salford, Salford, UK

Full Bibliographic Reference for this paper
F. Marir, I. Watson, "CBRefurb: A Case-Based Building Refurbishment Cost Estimator and Decision Support System", in B.H.V. Topping, (Editor), "Developments in Artificial Intelligence for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 231-236, 1995. doi:10.4203/ccp.35.12.2
Abstract
This paper highlights the strategic importance of the cost estimation of building refurbishment work and the need for IT tools to support managers in their decisions to go for refurbishment or redevelopment. An investigation amongst the North West councils has confirmed this need and has shown that the domain is too complex to design an expert system using model-based reasoning (MBR). As a result, an expert system (CBRefurb) which estimates the cost of refurbishing buildings and provides decision support for construction managers is designed. This system is being implemented using a relatively new paradigm called Case-Based Reasoning (CBR). CBR is chosen for several reasons. The complexity and the uncertainty that characterise building refurbishment makes it difficult to estimate the costs using model-based reasoning. In addition, since refurbishment estimators use previous similar work to produce estimates it is an ideal problem for CBR.

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