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Mass appraisal of real estate is a complex problem
because of multiple criteria. Developed technologic methods
provide a solution by transforming into the form of simple and
easy. Multiple Regression Analysis (MRA) is frequently used in
academic and practice studies in the world and our country. New
method quest continues according to recent advances in computer
technology. Artificial Neural Network (ANN) which is one of the
artificial intelligence methods should investigate in order to use in
the valuation because it can imitate human brain.
The aim of this study is to estimate with ANN method the value
of real estate. The study data consisted of the market samples
concerning the plots in Centre Neighborhood of Konya. The data
of the 558 samples were collected as main headings in the form of
Legal, Physical, Locational and Neighborhood Features. The data
set was separated for 70% training and 30% test. The market
values of the plots were forecasted by using 70% training data with
ANN and MRA methods and compared by testing 30% data in
both methods. According to the results, it has seemed that success
of ANN method is higher than the success of MRA method.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
Fatma Bunyan Unel
Şükran Yalpır
Appraisal of real estates which have a large important
for the country economics is pretty a hard occupation field. The
value of real estate indicates important level changes in
accordance with location and neighborhood features of their
places apart from legal and physical factors. Using value
prediction by explaining as mathematical these changes is a
complex problem. It is appropriate to use Geographical
Information Systems (GIS) application because of the size of the
study area in real estate valuation and the need to integrate the
attribute information into the map.
The purpose of this study is to provide using neighborhood
features affecting the value of real estate for mass appraisal. In
Centre Neighborhood of Konya, the neighborhood features were
taken into account, standardized with the help of GIS software by
producing the prediction and thematic maps in form of simple and
easy and made the ready form for valuation analysis. These maps
will be able to use as the base in all practices of valuation from
taxation to expropriation.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
Şükran Yalpır
Fatma Bunyan Unel