인공지능 (AI) 기반 섹터별 부동산 수익률 결정 모델 연구 - 글로벌 5개 도시를 중심으로 (서울, 뉴욕, 런던, 파리, 도쿄)

• Published in: 品質經營學會誌 Vol. 52; no. 3; pp. 429 - 457
• Main Authors: 이원부, Wonboo Lee, 이지수, Jisoo Lee, 김민상, Minsang Kim
• Format: Journal Article
• Language: Korean
• Published: 한국품질경영학회 30.09.2024
• Subjects: AI; Data Collection and Preprocessing; Profit Determination Model; Real Estate; Real World Asset; Result Analysis and Evaluation; Result Interpretation and Conclusion; RWA; 학제간연구; Result Analysis and Evaluation; Result Interpretation and Conclusion; Real Estate; RWA(Real World Asset); Profit Determination Model; AI; Data Collection and Preprocessing
• ISSN: 1229-1889; 2287-9005
• DOI: 10.7469/JKSQM.2024.52.3.429

Purpose: This study aims to provide useful information to real estate investors by developing a profit determination model using artificial intelligence. The model analyzes the real estate markets of six selected cities from multiple perspectives, incorporating characteristics of the real estate market, economic indicators, and policies to determine potential profits. Methods: Data on real estate markets, economic indicators, and policies for five cities were collected and cleaned. The data was then normalized and split into training and testing sets. An AI model was developed using machine learning algorithms and trained with this data. The model was applied to the six cities, and its accuracy was evaluated using metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-squared by comparing predicted profits to actual outcomes. Results: The profit determination model was successfully applied to the real estate markets of six cities, showing high accuracy and predictability in profit forecasts. The study provided valuable insights for real estate investors, demonstrating the model's utility for informed investment decisions. Conclusion: The study identified areas for future improvement, suggesting the integration of diverse data sources and advanced machine learning techniques to enhance predictive capabilities.