Cost estimation model for building projects using case-based reasoning

Abstract

The case-based reasoning (CBR) method can be an effective means of utilizing knowledge gained from past experiences to estimate cost in construction. It has also been observed that CBR can enhance the accuracy of construction cost estimates. However, there are challenges related to the process of retrieving knowledge and information that still need to be addressed. One challenge is the computation of similarity and another is the assignment of the attribute weight values. To address these challenges, this paper develops a CBR cost estimate model for building projects using a Euclidean distance concept and genetic algorithms. Consequently, it was found that this model can enhance the accuracy of cost estimation and act as a basis for further research on the fundamentals of the case-based reasoning method.