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Journal of Korean Society for Quality Management > Volume 52(3); 2024 > Article
Journal of Korean Society for Quality Management 2024;52(3): 429-457.
doi: https://doi.org/10.7469/JKSQM.2024.52.3.429
인공지능 (AI) 기반 섹터별 부동산 수익률 결정 모델 연구- 글로벌 5개 도시를 중심으로 (서울, 뉴욕, 런던, 파리, 도쿄) -
이원부1, 이지수1, 김민상2
1동국대학교 핀테크블록체인학과 인공지능 전공
2주식회사 위펀딩
A Study on AI-Based Real Estate Rate of Return Decision Models of 5 Sectors for 5 Global Cities: Seoul, New York, London, Paris and Tokyo
Wonboo Lee1, Jisoo Lee1, Minsang Kim2
1Dongkuk University
2Wefunding Corp.
Correspondence  Wonboo Lee ,Email: keziah@inha.ac.kr
Received: June 3, 2024; Revised: June 25, 2024   Accepted: July 3, 2024.  Published online: September 30, 2024.
ABSTRACT
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.
Key Words: Real Estate, RWA(Real World Asset), Profit Determination Model, AI, Data Collection and Preprocessing, Result Analysis and Evaluation, Result Interpretation and Conclusion
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