CASPIAN JOURNAL
MANAGEMENT AND HIGH TECHNOLOGIES
FORECASTING THE VALUE OF REAL ESTATE ON THE BASIS OF A COMPREHENSIVE ANALYSIS OF ITS PROPERTIES
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Read | Savina Oksana V., Malikov Vitaliy P., Sadovnikova Natalia P., Parygin Danila S., Mityagin Sergey A., Voronin Dmitry Yu. FORECASTING THE VALUE OF REAL ESTATE ON THE BASIS OF A COMPREHENSIVE ANALYSIS OF ITS PROPERTIES // Caspian journal : management and high technologies. — 2019. — №4. — pp. 60-70. |
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Savina Oksana V. - Senior Lecturer, Volgograd State Technical University, 28 Lenin Ave., Volgograd, 400005, Russian Federation, nov1984@yandex.ru
Malikov Vitaliy P. - post-graduate student, Volgograd State Technical University, 28 Lenin Ave., Volgograd, 400005, Russian Federation, axalter20@gmail.com
Sadovnikova Natalia P. - Doct. Sci. (Engineering), Associate Professor, Volgograd State Technical University, 28 Lenin Ave., Volgograd, 400005, Russian Federation, npsn1@ya.ru
Parygin Danila S. - Cand. Sci. (Engineering), Associate Professor, Volgograd State Technical University, 28 Lenin Ave., Volgograd, 400005, Russian Federation, dparygin@gmail.com
Mityagin Sergey A. - ITMO University, 14 Birzhevaya line, Saint Petersburg, 199034, Russian Federation, mityagin@itmo.ru
Voronin Dmitry Yu. - Sevastopol State University, 33 Universitetskaya St., Sevastopol, 299053, Russian Federation, voronin@sevsu.ru
The role of real estate in the study of urban infrastructure development and the development of the country as a whole is substantiated in the paper. A real estate object is considered as a system with certain characteristics, the main of which is a cost. The cost describes the result of real estate object assessment in the presence of a large number of criteria. Its value is influenced by some criteria, which are divided into two main groups: external and internal. The basic approaches to building a market valuation of a property based on various types of machine learning are considered. A new approach to determining the value of real estate based on a comprehensive analysis of its properties is proposed. The approach is based on a combination of the binary coding method of the qualitative characteristics of a real estate object, cluster analysis to determine objects of the same type and regression analysis to build a value forecast for the particular real estate object.
Key words: объект недвижимости, рынок недвижимости, рыночная стоимость объекта недвижимости, машинное обучение, бинарное кодирование, кластерный анализ, estate object, estate market, market value of the property, machine learning, binary coding, cluster analysis