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The real estate has an important position
economically in the world. Proper valuation of the real estate
is important for the country's economy. For the real estate
valuation, it is necessary to know well the concept of value
related to real estates and the factors, which affect the real
estate value around the area. With the development of
computer technology, it is possible to reach quick and
accurate results by making detailed analyzes. In recent years,
developments in artificial intelligence technologies have
made artificial intelligence methods more attractive in real
estate valuation. Also, advanced geographical information
system (GIS) technology has started to use extensively in the
real estate valuation. Thus, the creation of the databases,
which has predominantly spatial information, for real estates
increased the role of GIS in real estate valuation methods.
In this study, positional analysis of agricultural data in the
GIS environment was conducted and the factors affecting
depreciation were examined. Artificial neural networks
model is developed by data that are prepared in GIS
environment. Subsequently, the success of the predicted
outcome was assessed. As a result of this work is aimed to
obtain accurate information about the value of agricultural
land using mathematical modeling. The results show that real
estate prediction study using ANN was in good agreement
with absolute success value of 93% and correlation
coefficient (R2) value of %76.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
Şükran Yalpır
Osman Orhan
Hari̇ka Ülkü
Gamze Sarkım
Güneri Ervural