건축물 해체공사비 예측 모델 개발

Abstract

Considering rapid increase of the scale and the number of building demolition, proper cost prediction on the demolition work will become more important. However, the existing estimation methods based on the standard quantities per unit or experts’ experience have the limitations in terms of the accuracy and reliability.

Thus, this study proposed a cost prediction model for building demolition work by using multiple regression analysis technique based on the historical data. In order to achieve the purpose of the research, 27 historical data were collected from the experts survey. The contents of the survey include the information of actual construction costs and 13 factors affecting the cost fluctuation of each demolition site. Based on the collected information, 6 regression models using quantitative and/or qualitative factors were constructed and verified.

As a result, the regression models showed the average error rates of from about 6% to 43%. Of these models, model 5 using both quantitative and qualitative variables and model 6 using various qualitative variables showed relatively low error rates that may be acceptable as a predictive model. Other models can also be utilized for approximate estimation on the early stages of the project.

The proposed models can provide more accurate and reliable prediction results compared to the existing estimattion methods as well as are easy to use in practice. The results of this study can contribute to minimizing the risk by inaccurate cost prediction and proper cost estimation as well as conducting proper cost estimation and related criteria improvement.