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Title: Using svr and mra methods for real estate valuation in the smart cities
Authors: Akar, Ali Utku
Yalpır, S.
Keywords: Features
Real Estate Valuation
Valuation Model for Smart Cities and Urban
Office buildings
Population statistics
Regression analysis
Economic development
Multi-regression analysis
Population growth
Real estate valuations
Support vector regressions
Valuation model
Valuation model for smart city and urban
Value estimation
Smart city
Issue Date: 2021
Publisher: International Society for Photogrammetry and Remote Sensing
Abstract: Determination of real estate value plays a very critical role in economic development and basic needs of people. Increasing demand for real estate together with population growth is making it difficult to determine real estate value. In applications where real estate is the main subject, such as urban activities, smart cities and urbanization, urban information system and valuation systems, model-based value estimations are essential for effective land/real estate policy. The type of real estate and impact degree of features depending on the type should be known as well as value estimation. It will be beneficial to follow a method that both determines the real estate value and factor impact degree. With the studies to be carried out using such methods, both region-specific valuation models can be created and the model is established with the optimum variable. This paper aimed to determine real estate value by using Support Vector Regression (SVR) and Multi Regression Analysis (MRA) methods for effective real estate management. Besides, both methods were examined by revealing the impact degrees of features that affect the value. The methods were applied to 319 parcels in Konya. For each parcel, 31 land features and market values were collected. The parcel data collected since 2018 were included in the models. From the results, the RBF-SVR model reached the highest R2 value with 0.88, while the MRA model reached 0.86. © Author(s) 2021. CC BY 4.0 License.
Description: 6th International Conference on Smart City Applications -- 27 October 2021 through 29 October 2021 -- -- 175815
ISSN: 16821750
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections

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