UNIV. NEWS. NORTH-CAUCAS. REG. TECHNICAL SCIENCES SERIES. 2016; 3: 38-45
http://dx.doi.org/10.17213/0321-2653-2016-3-38-45
NEURAL NETWORK DATA ANALYSIS METHODS IN REAL ESTATE VALUATION
Surkov Fedor Alekseevich – Candidate of Physical and Mathematical Sciences, assistant professor, head of department «Global Information Systems»,
Petkova Natalia Vinediktovna – Candidate of Economic Sciences, assistant professor,
Sukhovskiy Sergey Fedorovich – post-graduate student,
Abstract
This article deals with the problems of real estate market control in the absence of a representative set of data for modeling the real estate market. We analyzed the traditional methods of data analysis and set their shortcomings. And revealed the necessity of the use of modern innovative methods, built on the basis of neural networks. On the basis of the research the author proposes to develop a methodology of real estate valuation, based on the mechanisms of data mining, as well as a comparison of the constructed real estate valuation model with the traditional statistical model.
Keywords: property valuation; neural network Kohonen; regression model.
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