| Title |
Investigation of Prediction of House Price Change in Seoul based on Demographics With Back Propagation Algorithm |
| Authors |
송영서(Young Suh Song) ; 김현우(Hyunwoo Kim) ; 조원선(One-Sun Cho) |
| DOI |
https://doi.org/10.5573/ieie.2020.57.10.27 |
| Keywords |
서울특별시; 주택가격; 머신러닝; 인구통계학; 인공지능 |
| Abstract |
In this paper, housing price in Seoul of Republic of Korea was predicted by utilizing annual birthrate data in Republic of Korea and machine learning algorithm. In order to conduct more accurate prediction, a back propagation algorithm was used among machine learning algorithms, and virtual GDP growth rate and expected life extension rate were considered. As a result, house price in Seoul is expected to increase steadily until 2025, and remain almost unchanged from 2025 to 2033, and then fall again after 2033. Eventually, it was expected that the house price of Seoul will return to a level similar to current house price of Seoul. This result was due to decrease in the number of people over the age of 25 from low fertility phenomenon, which results in decrease in demand for house. |