A Real Estate Appraisal Model with Artificial Neural Networks and Fuzzy Logic: A Local Case Study of Samsun City

Mehmet Emin Tabar (), Aziz Sisman () and Yasemin Sisman ()
Additional contact information
Mehmet Emin Tabar: Bitlis Eren University
Aziz Sisman: Ondokuz Mayis University
Yasemin Sisman: Ondokuz Mayis University

International Real Estate Review, 2023, vol. 26, issue 4, 569-585

Abstract: There have been great innovations in the field of real estate appraisal which have replaced the classical methods by recently established modern methods that involve computer technologies known as artificial intelligence. here are several artificial intelligent methods like fuzzy logic and artificial neural networks. In this study, two different real estate appraisal applications that are based on the artificial neural network and fuzzy logic methods are compared. An actual data set is taken from real estate agencies to develop a real estate appraisal model in Samsun city in Turkey. All of the real estate data belong to a certain time interval in May 2020. The selected parameters are scored by a valuation expert and the scores are then subjected to normalization. The obtained values are inputted into a fuzzy logic and artificial neural networks editor in MATLAB software and the valuation model is created. The values we obtain from the artificial neural networks and fuzzy logic are compared with actual sales data. It is observed that using these methods in real estate appraisal provides advantages in terms of time, cost and tangibility, as well as the means to create large database for real estate appraisal in a certain region.

Keywords: Artificial neural networks; Fuzzy logic; Artificial intelligence; Real estate appraisal (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.gssinst.org/irer/wp-content/uploads/202 ... l-Networks-Tabar.pdf Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ire:issued:v:26:n:04:2023:p:569-585

Ordering information: This journal article can be ordered from
Global Social Science Institute, 9200 Corporate Blvd., Suite 420 Rockville, MD 20850
https://www.gssinst.org/gssinst/index.html

Access Statistics for this article

International Real Estate Review is currently edited by Professor Sing Tien Foo and Professor Ko Wang

More articles in International Real Estate Review from Global Social Science Institute Global Social Science Institute, 9200 Corporate Blvd., Suite 420 Rockville, MD 20850.
Bibliographic data for series maintained by IRER Graduate Assistant/Webmaster ().