Predicting Maintenance and Rehabilitation Cost for Buildings Based on Artificial Neural Network and Fuzzy Logic

Abstract

In this paper, the study aims to develop a model for predicting and budgeting maintenance and rehabilitation projects costs for residential buildings throughout their life cycle based on artificial neural network, fuzzy logic and statistical techniques (multi-layer regression). Data consisting of bills of quantities were collected from local Algerian building construction agencies. The principle of costing significant items and work packages has been applied to optimize accurate and efficient document contract model. The results of the research show that neural network has more accuracy with 97% than the multi-layer regression analysis model.