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

Department of Civil Engineering, University 20 Aout 1955-Skikda, Faculty of Technology, LMGHU Laboratory, BP. 26, El-Hadaiek Street, 21 000, Skikda, Algeria

E-mail Address: amiraotm@hotmail.fr

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Mohamed Bouabaz

Department of Civil Engineering, University 20 Aout 1955-Skikda, Faculty of Technology, LMGHU Laboratory, BP. 26, El-Hadaiek Street, 21 000, Skikda, Algeria

E-mail Address: mbouabaz@hotmail.fr

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, and

Assem Al-Hajj

Department of Civil and Architectural Engineering, Applied Science University, Bahrain

E-mail Address: Assem.al-hajj@asu.edu.bh

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https://doi.org/10.1142/S1469026820500017Cited by:3 (Source: Crossref)

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.

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