Construction cost prediction on the basis of multiple parameters using case-based reasoning method

摘要

Nowadays, case-based reasoning (CBR) can be viewed as an effective and efficient method for cost prediction for building construction. Even if users have not very much experienced all the cases of knowledge base or database, this method makes it possible to retrieve the information of similar or exact cases, which are known to them, for new experiences. However, there are challenges related to the rapid retrieval process from the database library. One of the most important retrieval processes is the computation of similarity measures. With these issues, this research work attempts to build CBR in terms of similarity measuring method based on the concept of Euclidean distance and Chebyshev distance. The novelty of this paper is enhancing the accuracy of cost prediction as well as checking the effectiveness of the CBR model and both are relevant to academia and industry. In order to obtain the result, I have used indigenous tool.