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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 IX.3

A Knowledge-Based Advisory System for the Diagnosis and Repair of Subsidence Damage

C.J. Anumba, D. Scott and C.A.G. Webster

School of Science and Technology, University of Teesside, Middlesbrough, UK

Full Bibliographic Reference for this paper
C.J. Anumba, D. Scott, C.A.G. Webster, "A Knowledge-Based Advisory System for the Diagnosis and Repair of Subsidence Damage", in B.H.V. Topping, (Editor), "Developments in Artificial Intelligence for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 169-175, 1995. doi:10.4203/ccp.35.9.3
Abstract
An important aspect of the work of many UK engineers is the diagnosis and repair of subsidence damage to residential buildings. This has recorded significant growth over the last twenty years. With this growth has come the evolution of a major industry dedicated to dealing with subsidence cases. Accuracy in subsidence diagnosis and the specification of effective repairs require a good deal of practical experience and engineering judgment. Knowledge-based systems have emerged as useful tools for problem-solving in situation is such as this where human expertise is required. This paper describes a knowledge-based advisory system which is intended to improve the management of subsidence cases by providing engineers with intelligent advice at all stages of the management process. This is expected to result in remedial measures which are: based on more accurate diagnoses, more effective, more economic in the long-term, and better quality assured.

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