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http://dx.doi.org/10.6106/KJCEM.2020.21.6.113

Development of DL-MCS Hybrid Expert System for Automatic Estimation of Apartment Remodeling  

Kim, Jun (Department of Architectural Engineering, Ajou University)
Cha, Heesung (Department of Architectural Engineering, Ajou University)
Publication Information
Korean Journal of Construction Engineering and Management / v.21, no.6, 2020 , pp. 113-124 More about this Journal
Abstract
Social movements to improve the performance of buildings through remodeling of aging apartment houses are being captured. To this end, the remodeling construction cost analysis, structural analysis, and political institutional review have been conducted to suggest ways to activate the remodeling. However, although the method of analyzing construction cost for remodeling apartment houses is currently being proposed for research purposes, there are limitations in practical application possibilities. Specifically, In order to be used practically, it is applicable to cases that have already been completed or in progress, but cases that will occur in the future are also used for construction cost analysis, so the sustainability of the analysis method is lacking. For the purpose of this, we would like to suggest an automated estimating method. For the sustainability of construction cost estimates, Deep-Learning was introduced in the estimating procedure. Specifically, a method for automatically finding the relationship between design elements, work types, and cost increase factors that can occur in apartment remodeling was presented. In addition, Monte Carlo Simulation was included in the estimation procedure to compensate for the lack of uncertainty, which is the inherent limitation of the Deep Learning-based estimation. In order to present higher accuracy as cases are accumulated, a method of calculating higher accuracy by comparing the estimate result with the existing accumulated data was also suggested. In order to validate the sustainability of the automated estimates proposed in this study, 13 cases of learning procedures and an additional 2 cases of cumulative procedures were performed. As a result, a new construction cost estimating procedure was automatically presented that reflects the characteristics of the two additional projects. In this study, the method of estimate estimate was used using 15 cases, If the cases are accumulated and reflected, the effect of this study is expected to increase.
Keywords
Automatic Estimation; Schematic Estimation; Aged Apartment Remodeling; Deep Learning;
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Times Cited By KSCI : 6  (Citation Analysis)
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