Development of a decision support model for determining the target multi-family housing complex for green remodeling using data mining techniques

To achieve the national CO₂ emission reduction target in the building sector, green remodeling of deteriorated buildings with a low building energy efficiency level should be carried out. There is no reasonable decision support model for green remodeling, however, that is capable of determining the target building, which has low energy performance, from the viewpoint of the non-expert building owners and policymakers. To solve this problem, this study developed a decision support model for determining the target multi-family housing complex (MFHC) for green remodeling using data mining techniques. Specifically, a total of 589 MFHCs were classified into three groups using a decision tree. Based on the operational rating system, the CO₂ emission (CE) intensity by group was analyzed, and the results showed that Case No. 1,089 (0.0368 tCO₂/m²) was the target MFHC where green modeling needed to be performed first. Also, most of the 88 MFHCs belong to grade E, the lowest grade in terms of CE intensity, were located in specific regions (i.e., Gangnam-gu, Seocho-gu, etc.). Thus, the developed decision support model can be used to determine the regions with a high demand for green remodeling, and to establish an efficient government budget.