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A maintainability grading system using artificial neural networks which aids in enhancing decision-making of wet area design is derived in this paper. The model was derived from comprehensive condition surveys of 450 tall buildings and in-depth assessment of a further 120 tall buildings and face-to-face interviews with the relevant building professionals. 16 important risk factors were identified and tested according to their sensitivity in affecting maintainability scoring for wet areas. Thedoi:10.1080/00038628.2004.9697022 fatcat:ugeqw2at4jdqrgenqbe3blsyju