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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 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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