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.

Details

Title
USING SVR AND MRA METHODS FOR REAL ESTATE VALUATION IN THE SMART CITIES
Author
Akar, A U 1 ; Yalpir, S 1 

 Department of Geomatics Engineering, Konya Technical University, 42100, Konya, Turkey; Department of Geomatics Engineering, Konya Technical University, 42100, Konya, Turkey 
Pages
21-26
Publication year
2021
Publication date
2021
Publisher
Copernicus GmbH
ISSN
16821750
e-ISSN
21949034
Source type
Conference Paper
Language of publication
English
ProQuest document ID
2612629943
Copyright
© 2021. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.