Improved similarity measure in case-based reasoning: a case study of construction cost estimation. Issue 2 (21st November 2019)

• Record Type: Journal Article
• Authors: Hyung, Won-Gil; Kim, Sangyong; Jo, Jung-Kyu
• Is Part Of: Engineering, construction and architectural management. Volume 27:Issue 2(2020)
• Page Start: 561
• Page End: 578
• Publication Date: 2019-11-21
• Subjects: Knowledge management -- Construction -- Decision support systems -- Estimating; Construction industry -- Management -- Periodicals; Engineering -- Management -- Periodicals; Engineering -- Periodicals; Building -- Periodicals; 624.068
• DOI: 10.1108/ECAM-01-2019-0035
• Languages: English
• ISSNs: 0969-9988

Abstract

Abstract : Purpose: Applied a hybrid approach using genetic algorithms (GAs) for a case-based retrieval process in order to increase the overall improved cost accuracy for a case-based library. The paper aims to discuss this issue. Design/methodology/approach: A weight optimization approach using case-based reasoning (CBR) with proposed GAs for developing the CBR model. GAs are used to investigate optimized weight generation with an application to real project cases. Findings: The proposed CBR model can reduce errors consistently, and be potentially useful in the early financial planning stage. The authors suggest the developed CBR model can provide decision-makers with accurate cost information for assessing and comparing multiple alternatives in order to obtain the optimal solution while controlling cost. Originality/value: The system can operate with more accuracy or less cost, and CBR can be used to better understand the effects of factor interaction and variation during the developed system's process.