109 research outputs found
ΠΡΠ½ΠΎΠ²Π°Π½Π½ΡΠΉ Π½Π° Π·Π½Π°Π½ΠΈΡΡ ΠΏΠΎΠ΄Ρ ΠΎΠ΄ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΠΉ Π½Π΅ΡΡΡΠ½ΡΡ ΡΠ°Π·Π»ΠΈΠ²ΠΎΠ² Π½Π° ΠΏΠΎΠ²Π΅ΡΡ Π½ΠΎΡΡΡ Π·Π΅ΠΌΠ»ΠΈ
The oil industry carries enormous environmental risks and can cause consequences at different levels: water, air, soil, and, therefore, all living things on our planet. In this regard, forecasting the environmental consequences of oil spill accidents becomes relevant. Moreover, forecasting of oil spill accidents can be used to quickly assess the consequences of an accident that has already occurred, as well as to develop a plan of operational measures to eliminate possible accidents, facilities under construction, associated with the transportation, storage or processing of petroleum products. Consequently, the aim of this paper is to present a knowledge-based approach and its implementing system for forecasting the consequences of an accidental oil spills on the ground and groundwater. The novelty of the proposed approach is that it allows us to forecast the oil spill in a complex and systematic way. It consists of components for modelling geological environment (i.e., geological layers, oil spill form, the oil migration with groundwater), forecasting component for an oil spill and pollution mitigation component. Moreover, the forecasting component is based on expertsβ knowledge on oil spill. In addition, the paper presents a general architecture for the implementation of the proposed knowledge-based approach and its implementation into a prototype named SoS-Ground
ΠΡΠ½ΠΎΠ²Π°Π½Π½ΡΠΉ Π½Π° Π·Π½Π°Π½ΠΈΡΡ ΠΏΠΎΠ΄Ρ ΠΎΠ΄ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΠΉ Π½Π΅ΡΡΡΠ½ΡΡ ΡΠ°Π·Π»ΠΈΠ²ΠΎΠ² Π½Π° ΠΏΠΎΠ²Π΅ΡΡ Π½ΠΎΡΡΡ Π·Π΅ΠΌΠ»ΠΈ
The oil industry carries enormous environmental risks and can cause consequences at different levels: water, air, soil, and, therefore, all living things on our planet. In this regard, forecasting the environmental consequences of oil spill accidents becomes relevant. Moreover, forecasting of oil spill accidents can be used to quickly assess the consequences of an accident that has already occurred, as well as to develop a plan of operational measures to eliminate possible accidents, facilities under construction, associated with the transportation, storage or processing of petroleum products. Consequently, the aim of this paper is to present a knowledge-based approach and its implementing system for forecasting the consequences of an accidental oil spills on the ground and groundwater. The novelty of the proposed approach is that it allows us to forecast the oil spill in a complex and systematic way. It consists of components for modelling geological environment (i.e., geological layers, oil spill form, the oil migration with groundwater), forecasting component for an oil spill and pollution mitigation component. Moreover, the forecasting component is based on expertsβ knowledge on oil spill. In addition, the paper presents a general architecture for the implementation of the proposed knowledge-based approach and its implementation into a prototype named SoS-Ground.ΠΠ΅ΡΡΡΠ½Π°Ρ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΡ ΡΠΎΠΏΡΡΠΆΠ΅Π½Π° Ρ ΠΎΠ³ΡΠΎΠΌΠ½ΡΠΌΠΈ ΡΠΊΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΡΠΈΡΠΊΠ°ΠΌΠΈ ΠΈ ΠΌΠΎΠΆΠ΅Ρ ΠΏΡΠΈΠ²Π΅ΡΡΠΈ ΠΊβ―ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΡΠΌ Π½Π° ΡΠ°ΠΌΡΡ
ΡΠ°Π·Π½ΡΡ
ΡΡΠΎΠ²Π½ΡΡ
. ΠΡΠΎ ΠΈΠΌΠ΅Π΅Ρ ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠ΅ ΠΊΠ°ΠΊ ΠΊ Π²ΠΎΠ΄Π΅, Π²ΠΎΠ·Π΄ΡΡ
Ρ, ΠΏΠΎΡΠ²Π΅, ΡΠ°ΠΊ ΠΈ ΠΊΠΎ Π²ΡΠ΅ΠΌ ΠΆΠΈΠ²ΡΠΌ ΡΡΡΠ΅ΡΡΠ²Π°ΠΌ Π½Π° Π½Π°ΡΠ΅ΠΉ ΠΏΠ»Π°Π½Π΅ΡΠ΅. Π ΡΡΠΎΠΉ ΡΠ²ΡΠ·ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠΊΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΠΉ ΠΏΡΠΈ Π°Π²Π°ΡΠΈΠΉΠ½ΡΡ
ΡΠ°Π·Π»ΠΈΠ²Π°Ρ
Π½Π΅ΡΡΠΈ ΡΠ²Π»ΡΠ΅ΡΡΡ Π²Π΅ΡΡΠΌΠ° Π°ΠΊΡΡΠ°Π»ΡΠ½ΡΠΌ. ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ Π°Π²Π°ΡΠΈΠΉΠ½ΡΡ
ΡΠ°Π·Π»ΠΈΠ²ΠΎΠ² Π½Π΅ΡΡΠΈ ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΎ Π΄Π»Ρ Π±ΡΡΡΡΠΎΠΉ ΠΎΡΠ΅Π½ΠΊΠΈ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΠΉ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΡΠΆΠ΅ ΠΏΡΠΎΠΈΠ·ΠΎΡΠ΅Π΄ΡΠ΅ΠΉ Π°Π²Π°ΡΠΈΠΈ, Π° ΡΠ°ΠΊΠΆΠ΅ Π΄Π»Ρ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΏΠ»Π°Π½Π° ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠ²Π½ΡΡ
ΠΌΠ΅ΡΠΎΠΏΡΠΈΡΡΠΈΠΉ ΠΏΠΎ Π»ΠΈΠΊΠ²ΠΈΠ΄Π°ΡΠΈΠΈ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΡΡ
Π°Π²Π°ΡΠΈΠΉ, ΡΡΡΠΎΡΡΠΈΡ
ΡΡ ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ², ΡΠ²ΡΠ·Π°Π½Π½ΡΡ
Ρ ΡΡΠ°Π½ΡΠΏΠΎΡΡΠΈΡΠΎΠ²ΠΊΠΎΠΉ, Ρ
ΡΠ°Π½Π΅Π½ΠΈΠ΅ΠΌ ΠΈΠ»ΠΈ ΠΏΠ΅ΡΠ΅ΡΠ°Π±ΠΎΡΠΊΠΎΠΉ Π½Π΅ΡΡΠ΅ΠΏΡΠΎΠ΄ΡΠΊΡΠΎΠ². Π’Π°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ, ΡΠ΅Π»Ρ Π΄Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΡ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΠΈΡΡ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΡΠΉ Π½Π° Π·Π½Π°Π½ΠΈΡΡ
, ΠΈ ΡΠΈΡΡΠ΅ΠΌΡ Π΅Π³ΠΎ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ Π΄Π»Ρ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΠΉ Π°Π²Π°ΡΠΈΠΉΠ½ΡΡ
ΡΠ°Π·Π»ΠΈΠ²ΠΎΠ² Π½Π΅ΡΡΠΈ Π½Π° Π·Π΅ΠΌΠ»Π΅ ΠΈ Π² Π³ΡΡΠ½ΡΠΎΠ²ΡΡ
Π²ΠΎΠ΄Π°Ρ
. ΠΠΎΠ²ΠΈΠ·Π½Π° ΠΏΡΠ΅Π΄Π»Π°Π³Π°Π΅ΠΌΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° Π·Π°ΠΊΠ»ΡΡΠ°Π΅ΡΡΡ Π² ΡΠΎΠΌ, ΡΡΠΎ ΠΎΠ½ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎ ΠΈβ―ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°ΡΡ Π½Π΅ΡΡΡΠ½ΡΠ΅ ΡΠ°Π·Π»ΠΈΠ²Ρ. ΠΠΎΠ΄Ρ
ΠΎΠ΄ ΡΠΎΡΡΠΎΠΈΡ ΠΈΠ· ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠΎΠ² Π΄Π»Ρ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π³Π΅ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΡΠ΅Π΄Ρ (Ρ.Π΅. Π³Π΅ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ»ΠΎΠ΅Π², ΡΠΎΡΠΌΡ ΡΠ°Π·Π»ΠΈΠ²Π° Π½Π΅ΡΡΠΈ, ΠΌΠΈΠ³ΡΠ°ΡΠΈΠΈ Π½Π΅ΡΡΠΈ Π²ΠΌΠ΅ΡΡΠ΅ Ρ Π³ΡΡΠ½ΡΠΎΠ²ΡΠΌΠΈ Π²ΠΎΠ΄Π°ΠΌΠΈ), ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠ° ΠΏΠΎ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ°Π·Π»ΠΈΠ²Π° Π½Π΅ΡΡΠΈ ΠΈ ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠ°, ΡΠΌΡΠ³ΡΠ°ΡΡΠ΅Π³ΠΎ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΡ Π·Π°Π³ΡΡΠ·Π½Π΅Π½ΠΈΡ ΠΎΠΊΡΡΠΆΠ°ΡΡΠ΅ΠΉ ΡΡΠ΅Π΄Ρ. ΠΠΎΠΌΠΈΠΌΠΎ ΡΡΠΎΠ³ΠΎ, ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠΈΠΉ ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΡΡ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅, ΠΎΡΠ½ΠΎΠ²Π°Π½ Π½Π° ΡΠΊΡΠΏΠ΅ΡΡΠ½ΡΡ
Π·Π½Π°Π½ΠΈΡΡ
ΠΎ Π½Π΅ΡΡΡΠ½ΡΡ
ΡΠ°Π·Π»ΠΈΠ²Π°Ρ
. Π Π΄ΠΎΠΏΠΎΠ»Π½Π΅Π½ΠΈΠ΅, Π² Π΄Π°Π½Π½ΠΎΠΉ ΡΡΠ°ΡΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π° ΠΎΠ±ΡΠ°Ρ ΡΡΡΡΠΊΡΡΡΠ° ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π°, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ Π½Π° Π·Π½Π°Π½ΠΈΡΡ
, ΠΈ Π΅Π³ΠΎ ΠΎΡΡΡΠ΅ΡΡΠ²Π»Π΅Π½ΠΈΠ΅ Π² Π²ΠΈΠ΄Π΅ ΠΏΡΠΎΡΠΎΡΠΈΠΏΠ° SoS-Groun
Investigation of the effect of laser radiation parameters on the Structure and mechanical properties of parts obtained by the SLM technology from a titanium alloy
Anal Lymphogranuloma Venereum Infection Screening With IgA Anti-Chlamydia trachomatis-Specific Major Outer Membrane Protein Serology
Π Π°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΉ Π΄Π»Ρ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΈ ΡΡΡΡΠΊΡΡΡΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ
Statistical study of the primary real estate market is always associated with the problem that the object is in a constant, and very intense change, both in quantitative terms and in its internal content. Therefore, the issues of constant adaptation of statistical methodology in relation to the primary real estate market are relevant continuously. Among the tasks that are constantly in the field of statistical science and practice in relation to the primary real estate market are the following. First, a critical analysis of the content of the modern primary real estate market, which should allow to identify its fundamental features as an object of statistical research, to systematize the economic relations of the subjects of this market segment for a comprehensive statistical analysis of its functioning and development in any region of Russia. Secondly, it is the construction of analytical classifications of the primary real estate market, systematization of criteria for their construction, which should allow for a qualitative analysis of the structure of this market segment in the modern market economy. Third, the continuous improvement of the system of statistical indicators of the primary real estate market, whichΒ should be constantly supplemented by various blocks of indicators, the use of which will link the development of the primary real estate market with indicators of the standard of living of the population and socio-economic development of a particular region on the basis of the formation and ordering of its various subsystems, which will increase their consistency with indicators of living standards and socio-economic development. To Develop the theory and statistical methodology of the complex study of the primary real estate market in terms of the development of criteria for the division of the object into homogeneous groups by typological characteristics and the construction on their basis of statistical classifications necessary for the structural analysis of the primary real estate market. To obtain scientific results in this article, General scientific methods of cognition, such as scientific abstraction, analysis and synthesis, are used, since it is a question of dividing a single whole into typologically homogeneous complexes, the organic relationship between which ensures the integrity and unity of the studied object β the primary real estate market. In addition, the use of the statistical grouping method is considered throughout the work, as it is an applied application of typological criteria. The main classification features of economic assets traded in the primary real estate market of the region are Substantiated and formulated. The development of criteria for the typological division of the object allowed to build statistical classifications necessary for a comprehensive analysis of the structure and structural changes in the primary real estate market. In the scientific article deals with the problematic aspects of a statistical study of the primary real estate market in parts of its etymology on the basis of clear criteria against which to understand the quality and properties of the traded on its economic assets, to build a statistical classification. All this is a step in the first stage of the statistical study in the sequence that is classically considered by the General theory of statistics. Statistical classifications and groupings by typological features precede the science-intensive substantiation and application of complex mathematical and static methods for factor analysis and forecasting of primary real estate market indicators.Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π²ΡΠ΅Π³Π΄Π° ΡΠΎΠΏΡΡΠΆΠ΅Π½ΠΎ Ρ ΡΠΎΠΉ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠΎΠΉ, ΡΡΠΎ ΠΎΠ±ΡΠ΅ΠΊΡ Π½Π°Ρ
ΠΎΠ΄ΠΈΡΡΡ Π² ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎΠΌ, ΠΏΡΠΈΡΡΠΌ Π²Π΅ΡΡΠΌΠ° ΠΈΠ½ΡΠ΅Π½ΡΠΈΠ²Π½ΠΎΠΌ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΈ, ΠΊΠ°ΠΊ Π² ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΌ Π°ΡΠΏΠ΅ΠΊΡΠ΅, ΡΠ°ΠΊ ΠΈ Π² ΡΠ²ΠΎΡΠΌ Π²Π½ΡΡΡΠ΅Π½Π½Π΅ΠΌ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠΈ. ΠΠΎΡΡΠΎΠΌΡ ΠΈ Π²ΠΎΠΏΡΠΎΡΡ ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎΠΉ Π°Π΄Π°ΠΏΡΠ°ΡΠΈΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π°ΠΊΡΡΠ°Π»ΡΠ½Ρ Π½Π΅ΠΏΡΠ΅ΡΡΠ²Π½ΠΎ. Π‘ΡΠ΅Π΄ΠΈ Π·Π°Π΄Π°Ρ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎ Π½Π°Ρ
ΠΎΠ΄ΡΡΡΡ Π² ΠΏΠΎΠ»Π΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π½Π°ΡΠΊΠΈ ΠΈ ΠΏΡΠ°ΠΊΡΠΈΠΊΠΈ Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΠΌΠΎΠΆΠ½ΠΎ Π²ΡΠ΄Π΅Π»ΠΈΡΡ ΡΠ»Π΅Π΄ΡΡΡΠΈΠ΅. ΠΠΎ-ΠΏΠ΅ΡΠ²ΡΡ
, ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ ΠΊΡΠΈΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΡΡΠΎ Π΄ΠΎΠ»ΠΆΠ½ΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡΡ Π²ΡΡΠ²ΠΈΡΡ Π΅Π³ΠΎ ΠΏΡΠΈΠ½ΡΠΈΠΏΠΈΠ°Π»ΡΠ½ΡΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΠΊΠ°ΠΊ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ, ΡΠΈΡΡΠ΅ΠΌΠ°ΡΠΈΠ·ΠΈΡΠΎΠ²Π°ΡΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ²ΡΠ·ΠΈ ΡΡΠ±ΡΠ΅ΠΊΡΠΎΠ² Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ° ΡΡΠ½ΠΊΠ° Π΄Π»Ρ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° Π΅Π³ΠΎ ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π² Π»ΡΠ±ΠΎΠΌ ΡΠ΅Π³ΠΈΠΎΠ½Π΅ Π ΠΎΡΡΠΈΠΈ. ΠΠΎ-Π²ΡΠΎΡΡΡ
, ΡΡΠΎ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠ΅ Π°Π½Π°Π»ΠΈΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΉ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΡΠΈΡΡΠ΅ΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΡ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΠΈΡ
ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ, ΡΡΠΎ Π΄ΠΎΠ»ΠΆΠ½ΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡΡ ΠΏΡΠΎΠ²Π΅ΡΡΠΈ ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΡΡΡΠΊΡΡΡΡ Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ° ΡΡΠ½ΠΊΠ° Π² ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΡΡΠ½ΠΎΡΠ½ΠΎΠΉ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ. Π-ΡΡΠ΅ΡΡΠΈΡ
, ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎΠ΅ ΡΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠΈΡΡΠ΅ΠΌΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΠΊΠΎΡΠΎΡΠ°Ρ ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎ Π΄ΠΎΠ»ΠΆΠ½Π° Π΄ΠΎΠΏΠΎΠ»Π½ΡΡΡΡΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠΌΠΈ Π±Π»ΠΎΠΊΠ°ΠΌΠΈ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΊΠΎΡΠΎΡΡΡ
ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡ ΡΠ²ΡΠ·Π°ΡΡ ΡΠ°Π·Π²ΠΈΡΠΈΠ΅ ΡΡΠ½ΠΊΠ° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Ρ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠΌΠΈ ΡΡΠΎΠ²Π½Ρ ΠΆΠΈΠ·Π½ΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΈ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΎΠ³ΠΎ ΡΠ΅Π³ΠΈΠΎΠ½Π° Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠΏΠΎΡΡΠ΄ΠΎΡΠ΅Π½ΠΈΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
Π΅Π΅ ΠΏΠΎΠ΄ΡΠΈΡΡΠ΅ΠΌ, ΡΡΠΎ ΠΏΠΎΠ²ΡΡΠΈΡ ΠΈΡ
ΡΠΎΠ³Π»Π°ΡΠΎΠ²Π°Π½Π½ΠΎΡΡΡ Ρ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠΌΠΈ ΡΡΠΎΠ²Π½Ρ ΠΆΠΈΠ·Π½ΠΈ ΠΈ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ. Π¦Π΅Π»Ρ: Π Π°Π·Π²ΠΈΡΠΈΠ΅ ΡΠ΅ΠΎΡΠΈΠΈ ΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠ³ΠΎ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π² ΡΠ°ΡΡΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΡΠ°Π·Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΎΠ±ΡΠ΅ΠΊΡΠ° Π½Π° ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΡΠ΅ Π³ΡΡΠΏΠΏΡ ΠΏΠΎ ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΏΡΠΈΠ·Π½Π°ΠΊΠ°ΠΌ ΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠ΅ Π½Π° ΠΈΡ
ΠΎΡΠ½ΠΎΠ²Π΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΉ, Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΡΡ
Π΄Π»Ρ ΡΡΡΡΠΊΡΡΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ. ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ: ΠΠ»Ρ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡ Π½Π°ΡΡΠ½ΡΡ
ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π΄Π°Π½Π½ΠΎΠΉ ΡΡΠ°ΡΡΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΠΎΠ±ΡΠ΅Π½Π°ΡΡΠ½ΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΏΠΎΠ·Π½Π°Π½ΠΈΡ, ΡΠ°ΠΊΠΈΠ΅ ΠΊΠ°ΠΊ Π½Π°ΡΡΠ½Π°Ρ Π°Π±ΡΡΡΠ°ΠΊΡΠΈΡ, Π°Π½Π°Π»ΠΈΠ· ΠΈ ΡΠΈΠ½ΡΠ΅Π·, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΡΠ΅ΡΡ ΠΈΠ΄Π΅Ρ ΠΎ ΡΠ°Π·Π±ΠΈΠ΅Π½ΠΈΠΈ Π΅Π΄ΠΈΠ½ΠΎΠ³ΠΎ ΡΠ΅Π»ΠΎΠ³ΠΎ Π½Π° ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈ ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΡΠ΅ ΡΠΎΠ²ΠΎΠΊΡΠΏΠ½ΠΎΡΡΠΈ, ΠΎΡΠ³Π°Π½ΠΈΡΠ½Π°Ρ Π²Π·Π°ΠΈΠΌΠΎΡΠ²ΡΠ·Ρ ΠΌΠ΅ΠΆΠ΄Ρ ΠΊΠΎΡΠΎΡΡΠΌΠΈ ΠΈ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°Π΅Ρ ΡΠ΅Π»ΠΎΡΡΠ½ΠΎΡΡΡ ΠΈ Π΅Π΄ΠΈΠ½ΡΡΠ²ΠΎ ΠΈΠ·ΡΡΠ°Π΅ΠΌΠΎΠ³ΠΎ ΠΎΠ±ΡΠ΅ΠΊΡΠ° β ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ. ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, Π½Π° ΠΏΡΠΎΡΡΠΆΠ΅Π½ΠΈΠΈ Π²ΡΠ΅ΠΉ ΡΠ°Π±ΠΎΡΡ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π° Π³ΡΡΠΏΠΏΠΈΡΠΎΠ²ΠΎΠΊ, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΡΠ΅ΡΡ ΠΈΠ΄Π΅Ρ ΠΎ ΠΏΡΠΈΠΊΠ»Π°Π΄Π½ΠΎΠΌ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠΈ ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π΅Π΄ΠΈΠ½ΠΈΡ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ Π² ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΡΠ΅ Π³ΡΡΠΏΠΏΡ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ: ΠΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½Ρ ΠΈ ΡΡΠΎΡΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Π°ΠΊΡΠΈΠ²ΠΎΠ², ΠΎΠ±ΡΠ°ΡΠ°ΡΡΠΈΡ
ΡΡ Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ ΡΡΠ½ΠΊΠ΅ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΡΠ΅Π³ΠΈΠΎΠ½Π°. Π Π°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»Π° ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ, Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΡΠ΅ Π΄Π»Ρ Π²ΡΠ΅ΡΡΠΎΡΠΎΠ½Π½Π΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΡΡΡΡΠΊΡΡΡΡ ΠΈ ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΡΠ΄Π²ΠΈΠ³ΠΎΠ² Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ ΡΡΠ½ΠΊΠ΅ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ. ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅: Π Π½Π°ΡΡΠ½ΠΎΠΉ ΡΡΠ°ΡΡΠ΅ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ½ΡΠ΅ Π°ΡΠΏΠ΅ΠΊΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π² ΡΠ°ΡΡΠΈ Π΅Π³ΠΎ ΡΡΠΈΠΌΠΎΠ»ΠΎΠ³ΠΈΠ·Π°ΡΠΈΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΡΡΠΊΠΈΡ
ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π², ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠΈΡ
ΠΏΠΎΠ½ΡΡΡ ΠΊΠ°ΡΠ΅ΡΡΠ²ΠΎ ΠΈ ΡΠ²ΠΎΠΉΡΡΠ²Π° ΠΎΠ±ΡΠ°ΡΠ°ΡΡΠΈΡ
ΡΡ Π½Π° Π½Π΅ΠΌ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
Π°ΠΊΡΠΈΠ²ΠΎΠ², ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ. ΠΡΡ ΡΡΠΎ ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΠ°Π³ΠΎΠΌ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΠΏΠ΅ΡΠ²ΠΎΠ³ΠΎ ΡΡΠ°ΠΏΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π² ΡΠΎΠΉ Π΅Π³ΠΎ ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ, ΠΊΠΎΡΠΎΡΠ°Ρ ΠΊΠ»Π°ΡΡΠΈΡΠ΅ΡΠΊΠΈ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΎΠ±ΡΠ΅ΠΉ ΡΠ΅ΠΎΡΠΈΠ΅ΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ. Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΈ Π³ΡΡΠΏΠΏΠΈΡΠΎΠ²ΠΊΠΈ ΠΏΠΎ ΡΠΈΠΏΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΏΡΠΈΠ·Π½Π°ΠΊΠ°ΠΌ ΠΏΡΠ΅Π΄ΡΠ΅ΡΡΠ²ΡΡΡ Π½Π°ΡΠΊΠΎΠ΅ΠΌΠΊΠΎΠΌΡ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΠ»ΠΎΠΆΠ½ΡΡ
ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΎ-ΡΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² Π΄Π»Ρ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΡΠ°ΠΊΡΠΎΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ
Π‘ΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠ΅ ΠΈ Π³ΡΠ°Π½ΠΈΡΡ ΡΡΠ½ΠΊΠ° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΠΊΠ°ΠΊ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ
The primary real estate market is one of the youngest segments of the market economy in modern Russia. If the genesis of the modern secondary market was observed in the pre-reform period: barter relations in terms of urban housing, the purchase and sale of suburban areas were freely carried out, small suburban real estate, garage buildings, etc., the real market relations with the relevant legal framework in terms of ownership rights in the primary market became possible only with the change of economic formation. All participants in the rapidly emerging primary real estate market quickly became familiar with pricing, market conditions, utility criteria and many other parameters inherent in this market segment. However, issues of managing business processes on the primary market of real estate, including a balance of opportunities for sellers and customer needs, pricing, adequate information support to all management levels, still are a problem and remain open.Purpose. The relevance and social need for statistical study of the primary real estate market determined the purpose of scientific work as a clarification of the nature, content, boundaries and participants of the market in order to improve and develop statistical methodology.Materials and methods. To make the research and form the adequate conclusions when writing a scientific paper, the extensive material of theoretical, methodological and applied nature was used, the authors of which are both domestic and foreign scientists in the field of statistics, management, investment, marketing and technical sciences. The paper uses a wide range of general scientific methods of knowledge, the use of which together allowed to abstract from the non-essential aspects and mutually reinforcing factors that do not ultimately have a tangible impact on the state and dynamics of the primary real estate market - methods of abstraction and idealization; moving from the general laws of the real estate market, to form private conclusions concerning the segments and even objects of the primary real estate market as an object of statistical research β the method of deduction; to comprehend the object as a whole and at the same time as an interconnected mechanism represented by all its structural components β methods of analysis and synthesis; to conduct a comparative analysis of objects and identify possible vectors of the market development β methods of analogy and mental-symbolic modeling.Results. Qualitative analysis allowed to determine the place and importance of the primary real estate market in the entire system of multi-market economy; to identify the life cycle of the objects of the market and on their basis to structure it; to identify the factors of development of the primary real estate market, quantitative assessment of the impact of which will be subsequently given on the basis of regression analysis; to summarize the set of risks that determine the diverse variation of the primary real estate market. The development of statistical methodology for the study of the primary real estate market can be based only on a clear understanding of the nature and internal content of the studied object. At the same time, so sensitive to the market and general economic situation in the country and each region, the market is constantly changing: it does not have a stationary point. Therefore, it is necessary not only quantitative analysis of the object on the basis of statistical methods, but also continuous monitoring of all economic phenomena that contribute to the modification of the primary real estate market.ΠΠ΅ΡΠ²ΠΈΡΠ½ΡΠΉ ΡΡΠ½ΠΎΠΊ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΠ΄Π½ΠΈΠΌ ΠΈΠ· ΡΠ°ΠΌΡΡ
ΠΌΠΎΠ»ΠΎΠ΄ΡΡ
ΡΠ΅Π³ΠΌΠ΅Π½ΡΠΎΠ² ΡΡΠ½ΠΎΡΠ½ΠΎΠΉ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ Π² ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Π ΠΎΡΡΠΈΠΈ. ΠΡΠ»ΠΈ Π³Π΅Π½Π΅Π·ΠΈΡ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ Π²ΡΠΎΡΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π°Π±Π»ΡΠ΄Π°Π»ΡΡ Π΅ΡΠ΅ Π² Π΄ΠΎΡΠ΅ΡΠΎΡΠΌΠ΅Π½Π½ΡΠΉ ΠΏΠ΅ΡΠΈΠΎΠ΄: Π½ΠΎΡΠΈΠ» ΡΠΎΡΠΌΡ Π±Π°ΡΡΠ΅ΡΠ½ΡΡ
ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΉ Π² ΡΠ°ΡΡΠΈ Π³ΠΎΡΠΎΠ΄ΡΠΊΠΎΠ³ΠΎ ΠΆΠΈΠ»ΡΡ, ΡΠ²ΠΎΠ±ΠΎΠ΄Π½ΠΎ ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ»Π°ΡΡ ΠΊΡΠΏΠ»Ρ-ΠΏΡΠΎΠ΄Π°ΠΆΠ° Π΄Π°ΡΠ½ΡΡ
ΡΡΠ°ΡΡΠΊΠΎΠ², ΠΌΠ΅Π»ΠΊΠΎΠΉ Π·Π°Π³ΠΎΡΠΎΠ΄Π½ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, Π³Π°ΡΠ°ΠΆΠ½ΡΡ
ΡΠΎΠΎΡΡΠΆΠ΅Π½ΠΈΠΉ ΠΈ Ρ.Π΄., ΡΠΎ ΡΠ΅Π°Π»ΡΠ½ΡΠ΅ ΡΡΠ½ΠΎΡΠ½ΡΠ΅ ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡ Ρ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡΠΈΠΌ ΡΡΠΈΠ΄ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΎΠ±ΡΠ°ΠΌΠ»Π΅Π½ΠΈΠ΅ΠΌ Π² ΡΠ°ΡΡΠΈ ΠΏΡΠ°Π² ΡΠΎΠ±ΡΡΠ²Π΅Π½Π½ΠΎΡΡΠΈ Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ ΡΡΠ½ΠΊΠ΅ ΡΡΠ°Π»ΠΈ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½Ρ ΡΠΎΠ»ΡΠΊΠΎ ΡΠΎ ΡΠΌΠ΅Π½ΠΎΠΉ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΎΡΠΌΠ°ΡΠΈΠΈ. ΠΡΠ΅ ΡΡΠ°ΡΡΠ½ΠΈΠΊΠΈ Π±ΡΡΡΡΠΎ ΡΠΎΡΠΌΠΈΡΡΡΡΠ΅Π³ΠΎΡΡ ΡΡΠ½ΠΊΠ° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π΄ΠΎΠ²ΠΎΠ»ΡΠ½ΠΎ Π±ΡΡΡΡΠΎ ΡΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π»ΠΈΡΡ ΠΏΠΎ Π²ΠΎΠΏΡΠΎΡΠ°ΠΌ ΡΠ΅Π½ΠΎΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ, ΡΡΠ½ΠΎΡΠ½ΠΎΠΉ ΠΊΠΎΠ½ΡΡΠ½ΠΊΡΡΡΡ, ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΠΏΠΎΠ»Π΅Π·Π½ΠΎΡΡΠΈ ΠΈ ΠΌΠ½ΠΎΠ³ΠΈΠΌ Π΄ΡΡΠ³ΠΈΠΌ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠ°ΠΌ, ΠΏΡΠΈΡΡΡΠΈΠΌ Π΄Π°Π½Π½ΠΎΠΌΡ ΡΠ΅Π³ΠΌΠ΅Π½ΡΡ ΡΡΠ½ΠΊΠ°. ΠΠΌΠ΅ΡΡΠ΅ Ρ ΡΠ΅ΠΌ, ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ Π²ΠΎΠΏΡΠΎΡΠΎΠ² ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ°ΠΌΠΈ Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΌ ΡΡΠ½ΠΊΠ΅ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, Π²ΠΊΠ»ΡΡΠ°Ρ ΡΠ±Π°Π»Π°Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΡΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠ΅ΠΉ ΠΏΡΠΎΠ΄Π°Π²ΡΠΎΠ² ΠΈ ΠΏΠΎΡΡΠ΅Π±Π½ΠΎΡΡΠ΅ΠΉ ΠΏΠΎΠΊΡΠΏΠ°ΡΠ΅Π»Π΅ΠΉ, ΡΠ΅Π³ΡΠ»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ΅Π½ΠΎΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ, Π°Π΄Π΅ΠΊΠ²Π°ΡΠ½ΠΎΠ³ΠΎ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ Π²ΡΠ΅Ρ
ΡΠΏΡΠ°Π²Π»Π΅Π½ΡΠ΅ΡΠΊΠΈΡ
Π·Π²Π΅Π½ΡΠ΅Π², Π΄ΠΎ ΡΠΈΡ
ΠΏΠΎΡ Π½ΠΎΡΡΡ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ½ΡΠΉ Ρ
Π°ΡΠ°ΠΊΡΠ΅Ρ ΠΈ ΠΎΡΡΠ°ΡΡΡΡ ΠΎΡΠΊΡΡΡΡΠΌΠΈ.Π¦Π΅Π»Ρ. ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ ΠΈ ΠΎΠ±ΡΠ΅ΡΡΠ²Π΅Π½Π½Π°Ρ ΠΏΠΎΡΡΠ΅Π±Π½ΠΎΡΡΡ Π² ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΌ ΠΈΠ·ΡΡΠ΅Π½ΠΈΠΈ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΠΏΡΠ΅Π΄ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΠ»ΠΈ ΡΠ΅Π»Ρ Π½Π°ΡΡΠ½ΠΎΠΉ ΡΠ°Π±ΠΎΡΡ ΠΊΠ°ΠΊ ΡΡΠΎΡΠ½Π΅Π½ΠΈΠ΅ ΡΡΡΠ½ΠΎΡΡΠΈ, ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ, Π³ΡΠ°Π½ΠΈΡ ΠΈ ΡΡΠ°ΡΡΠ½ΠΈΠΊΠΎΠ² Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π² ΠΈΠ½ΡΠ΅ΡΠ΅ΡΠ°Ρ
ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ.ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΠ»Ρ Π²ΡΡΡΡΠ°ΠΈΠ²Π°Π½ΠΈΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π°Π΄Π΅ΠΊΠ²Π°ΡΠ½ΡΡ
Π²ΡΠ²ΠΎΠ΄ΠΎΠ² ΠΏΡΠΈ Π½Π°ΠΏΠΈΡΠ°Π½ΠΈΠΈ Π½Π°ΡΡΠ½ΠΎΠΉ ΡΡΠ°ΡΡΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ ΠΎΠ±ΡΠΈΡΠ½ΡΠΉ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π» ΡΠ΅ΠΎΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ, ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈ ΠΏΡΠΈΠΊΠ»Π°Π΄Π½ΠΎΠ³ΠΎ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠ°, Π°Π²ΡΠΎΡΠ°ΠΌΠΈ ΠΊΠΎΡΠΎΡΠΎΠ³ΠΎ ΡΠ²Π»ΡΡΡΡΡ, ΠΊΠ°ΠΊ ΠΎΡΠ΅ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠ΅, ΡΠ°ΠΊ ΠΈ Π·Π°ΡΡΠ±Π΅ΠΆΠ½ΡΠ΅ ΡΡΠ΅Π½ΡΠΉ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ, ΠΌΠ΅Π½Π΅Π΄ΠΆΠΌΠ΅Π½ΡΠ°, ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΉ, ΠΌΠ°ΡΠΊΠ΅ΡΠΈΠ½Π³Π°, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
Π½Π°ΡΠΊ. Π ΡΠ°Π±ΠΎΡΠ΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ ΡΠΈΡΠΎΠΊΠΈΠΉ ΠΊΡΡΠ³ ΠΎΠ±ΡΠ΅Π½Π°ΡΡΠ½ΡΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΏΠΎΠ·Π½Π°Π½ΠΈΡ, ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΊΠΎΡΠΎΡΡΡ
Π² ΡΠΎΠ²ΠΎΠΊΡΠΏΠ½ΠΎΡΡΠΈ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ Π°Π±ΡΡΡΠ°Π³ΠΈΡΠΎΠ²Π°ΡΡΡΡ ΠΎΡ Π½Π΅ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ
Π°ΡΠΏΠ΅ΠΊΡΠΎΠ² ΠΈ Π²Π·Π°ΠΈΠΌΠΎΠΏΠΎΠ³Π°ΡΠ°ΡΡΠΈΡ
Π΄ΡΡΠ³ Π΄ΡΡΠ³Π° ΡΠ°ΠΊΡΠΎΡΠΎΠ², Π½Π΅ ΠΎΠΊΠ°Π·ΡΠ²Π°ΡΡΠΈΡ
Π² ΠΊΠΎΠ½Π΅ΡΠ½ΠΎΠΌ ΠΈΡΠΎΠ³Π΅ ΠΎΡΡΡΠΈΠΌΠΎΠ³ΠΎ Π²Π»ΠΈΡΠ½ΠΈΡ Π½Π° ΡΠΎΡΡΠΎΡΠ½ΠΈΠ΅ ΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΡ ΡΡΠ½ΠΊΠ° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ β ΠΌΠ΅ΡΠΎΠ΄Ρ Π°Π±ΡΡΡΠ°ΠΊΡΠΈΠΈ ΠΈ ΠΈΠ΄Π΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ; ΠΏΠ΅ΡΠ΅ΠΉΠ΄Ρ ΠΎΡ ΠΎΠ±ΡΠΈΡ
Π·Π°ΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΠ΅ΠΉ ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΡΡΠΎΡΠΌΠΈΡΠΎΠ²Π°ΡΡ ΡΠ°ΡΡΠ½ΡΠ΅ Π²ΡΠ²ΠΎΠ΄Ρ, ΠΊΠ°ΡΠ°ΡΡΠΈΠ΅ΡΡ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠΎΠ² ΠΈ Π΄Π°ΠΆΠ΅ ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ² ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΠΊΠ°ΠΊ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ β ΠΌΠ΅ΡΠΎΠ΄ Π΄Π΅Π΄ΡΠΊΡΠΈΠΈ; ΠΏΠΎΡΡΠΈΡΡ ΠΎΠ±ΡΠ΅ΠΊΡ ΠΊΠ°ΠΊ Π΅Π΄ΠΈΠ½ΠΎΠ΅ ΡΠ΅Π»ΠΎΠ΅ ΠΈ ΠΎΠ΄Π½ΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎ ΠΊΠ°ΠΊ Π²Π·Π°ΠΈΠΌΠΎΡΠ²ΡΠ·Π°Π½Π½ΡΠΉ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌ, ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΡΠΉ Π²ΡΠ΅ΠΌΠΈ Π΅Π³ΠΎ ΡΡΡΡΠΊΡΡΡΠ½ΡΠΌΠΈ ΡΠΎΡΡΠ°Π²Π»ΡΡΡΠΈΠΌΠΈ β ΠΌΠ΅ΡΠΎΠ΄Ρ Π°Π½Π°Π»ΠΈΠ·Π° ΠΈ ΡΠΈΠ½ΡΠ΅Π·Π°; ΠΏΡΠΎΠ²Π΅ΡΡΠΈ ΡΡΠ°Π²Π½ΠΈΡΠ΅Π»ΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ² ΠΈ ΠΎΠ±ΠΎΠ·Π½Π°ΡΠΈΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΡΠ΅ Π²Π΅ΠΊΡΠΎΡΡ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° β ΠΌΠ΅ΡΠΎΠ΄Ρ Π°Π½Π°Π»ΠΎΠ³ΠΈΠΈ ΠΈ ΠΌΡΡΠ»Π΅Π½Π½ΠΎ-ΡΠΈΠΌΠ²ΠΎΠ»ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ» ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΡΡ ΠΌΠ΅ΡΡΠΎ ΠΈ Π·Π½Π°ΡΠ΅Π½ΠΈΠ΅ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π²ΠΎ Π²ΡΠ΅ΠΉ ΡΠΈΡΡΠ΅ΠΌΠ΅ ΠΌΠ½ΠΎΠ³ΠΎΡΠΊΠ»Π°Π΄Π½ΠΎΠ³ΠΎ ΡΡΠ½ΠΎΡΠ½ΠΎΠ³ΠΎ Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π°; ΠΎΠ±ΠΎΠ·Π½Π°ΡΠΈΡΡ ΠΆΠΈΠ·Π½Π΅Π½Π½ΡΠ΅ ΡΠΈΠΊΠ»Π° ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ² Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° ΠΈ Π½Π° ΠΈΡ
ΠΎΡΠ½ΠΎΠ²Π΅ ΡΡΡΡΠΊΡΡΡΠΈΡΠΎΠ²Π°ΡΡ Π΅Π³ΠΎ; ΠΎΠ±ΠΎΠ·Π½Π°ΡΠΈΡΡ ΡΠ°ΠΊΡΠΎΡΡ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½Π°Ρ ΠΎΡΠ΅Π½ΠΊΠ° Π²Π»ΠΈΡΠ½ΠΈΡ ΠΊΠΎΡΠΎΡΡΡ
Π±ΡΠ΄Π΅Ρ Π² ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠ΅ΠΌ Π΄Π°Π½Π° Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π°; ΠΎΠ±ΠΎΠ±ΡΠΈΡΡ ΡΠΎΠ²ΠΎΠΊΡΠΏΠ½ΠΎΡΡΡ ΡΠΈΡΠΊΠΎΠ², ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΡΡΠΈΡ
ΠΌΠ½ΠΎΠ³ΠΎΠΎΠ±ΡΠ°Π·Π½ΡΡ Π²Π°ΡΠΈΠ°ΡΠΈΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ.ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. Π Π°Π·Π²ΠΈΡΠΈΠ΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π΄Π»Ρ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ ΠΌΠΎΠΆΠ΅Ρ Π±Π°Π·ΠΈΡΠΎΠ²Π°ΡΡΡΡ ΡΠΎΠ»ΡΠΊΠΎ Π½Π° ΡΡΡΠΊΠΎΠΌ ΠΏΠΎΠ½ΠΈΠΌΠ°Π½ΠΈΠΈ ΡΡΡΠ½ΠΎΡΡΠΈ ΠΈ Π²Π½ΡΡΡΠ΅Π½Π½Π΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΈΠ·ΡΡΠ°Π΅ΠΌΠΎΠ³ΠΎ ΠΎΠ±ΡΠ΅ΠΊΡΠ°. ΠΡΠΈ ΡΡΠΎΠΌ ΡΠ°ΠΊΠΎΠΉ ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΡΠΉ ΠΊ ΡΡΠ½ΠΎΡΠ½ΠΎΠΉ ΠΊΠΎΠ½ΡΡΠ½ΠΊΡΡΡΠ΅ ΠΈ ΠΎΠ±ΡΠ΅ΠΉ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΈΡΡΠ°ΡΠΈΠΈ Π² ΡΡΡΠ°Π½Π΅ ΠΈ ΠΊΠ°ΠΆΠ΄ΠΎΠΌ ΡΠ΅Π³ΠΈΠΎΠ½Π΅ ΡΡΠ½ΠΎΠΊ, ΠΌΠ°Π½ΡΡΡΡ ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎ: Ρ Π½Π΅Π³ΠΎ Π½Π΅ Π±ΡΠ²Π°Π΅Ρ ΡΡΠ°ΡΠΈΠΎΠ½Π°ΡΠ½ΠΎΠΉ ΡΠΎΡΠΊΠΈ. ΠΠΎΡΡΠΎΠΌΡ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌ Π½Π΅ ΡΠΎΠ»ΡΠΊΠΎ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΎΠ±ΡΠ΅ΠΊΡΠ° Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ², Π½ΠΎ ΠΈ ΠΏΠΎΡΡΠΎΡΠ½Π½ΡΠΉ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³ Π²ΡΠ΅Ρ
ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ²Π»Π΅Π½ΠΈΠΉ, Π²Π½ΠΎΡΡΡΠΈΡ
ΡΠ²ΠΎΠΉ Π²ΠΊΠ»Π°Π΄ Π² ΠΌΠΎΠ΄ΠΈΡΠΈΠΊΠ°ΡΠΈΡ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΡΡΠ½ΠΊΠ° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ
Geoantineutrino Spectrum, 3He/4He-ratio Distribution in the Earth's Interior and Slow Nuclear Burning on the Boundary of the Liquid and Solid Phases of the Earth's Core
The description problem of geoantineutrino spectrum and reactor antineutrino
experimental spectrum in KamLAND, which takes place for antineutrino energy
\~2.8 MeV, and also the experimental results of the interaction of uranium
dioxide and carbide with iron-nickel and silicaalumina melts at high pressure
(5-10 GP?) and temperature (1600-2200C) have motivated us to consider the
possible consequences of the assumption made by V.Anisichkin and coauthors that
there is an actinid shell on boundary of liquid and solid phases of the Earth's
core. We have shown that the activation of a natural nuclear reactor operating
as the solitary waves of nuclear burning in 238U- and/or 232Th-medium (in
particular, the neutron- fission progressive wave of Feoktistov and/or
Teller-Ishikawa-Wood) can be such a physical consequence. The simplified model
of the kinetics of accumulation and burnup in U-Pu fuel cycle of Feoktistov is
developed. The results of the numerical simulation of neutron-fission wave in
two-phase UO2/Fe medium on a surface of the Earth's solid core are presented.
The georeactor model of 3He origin and the 3He/4He-ratio distribution in the
Earth's interior is offered. It is shown that the 3He/4He ratio distribution
can be the natural quantitative criterion of georeactor thermal power. On the
basis of O'Nions-Evensen-Hamilton geochemical model of mantle differentiation
and the crust growth supplied by actinid shell on the boundary of liquid and
solid phases of the Earth's core as a nuclear energy source (georeactor with
power of 30 TW), the tentative estimation of geoantineutrino intensity and
geoantineutrino spectrum on the Earth surface are given.Comment: 28 pages, 12 figures. Added text, formulas, figures and references.
Corrected equations. Changed content of some section
Π ΠΠΠΠ ΠΠ‘Π£ Π Π’ΠΠΠ ΠΠ’ΠΠ§ΠΠ‘ΠΠΠ₯ ΠΠΠΠ₯ΠΠΠΠ₯ Π ΠΠ¦ΠΠΠΠ ΠΠΠΠΠΠ ΠΠ€ΠΠ§ΠΠ‘ΠΠΠ ΠΠΠΠΠΠΠ‘ΠΠΠ‘Π’Π
The article deals with the theoretical estimates of demographic security issues. Analyzed different approaches to statistical evaluation of demographic security. An original system of statistical indicators of demographic security.Π ΡΡΠ°ΡΡΠ΅ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ ΡΠ΅ΠΎΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π²ΠΎΠΏΡΠΎΡΡ ΠΎΡΠ΅Π½ΠΊΠΈ Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ. ΠΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠ΅ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Ρ ΠΊ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΡΠ΅Π½ΠΊΠΈ Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ. ΠΠΎΡΡΡΠΎΠ΅Π½Π° ΠΎΡΠΈΠ³ΠΈΠ½Π°Π»ΡΠ½Π°Ρ ΡΠΈΡΡΠ΅ΠΌΠ° ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ
Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ
The article examines modern trends in vital statistics of Russia from the viewpoint of threats to national security; it includes quantitative analysis of interaction among demographic components of population change. The authors consider the role that Russia plays in global demographic processes and its position within the largest countries in the world by population size. Using statistical tools the paper evaluates modern trends in reproduction of population in Russia amid revealing demographic threats to the efficient socioeconomic development of the country. It also presents analysis of quantitative as well as qualitative characteristics of population replacement processes, which include total value and rate of childbearing, and quality of gene pool of the population. Statistical analysis of quantitative characteristics of mortality (i.e. indicators of mortality from external causes) served as the foundation for identifying modern trends in natural decrease of population in the Russian Federation.Π ΡΡΠ°ΡΡΠ΅ Ρ ΡΠΎΡΠΊΠΈ Π·ΡΠ΅Π½ΠΈΡ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΠ³ΡΠΎΠ· Π½Π°ΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠΉ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°ΡΡΡΡ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠ΅ ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΠΈ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ Π½Π°ΡΠΎΠ΄ΠΎΠ½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ Π² Π ΠΎΡΡΠΈΠΈ, ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ΅ΡΡΡ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΠΈΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ. ΠΡΠ΅Π½Π΅Π½Π° ΡΠΎΠ»Ρ Π ΠΎΡΡΠΈΠΈ Π² Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΡΡ
Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΡΠ°Ρ
, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΌΠ΅ΡΡΠΎ Π½Π°ΡΠ΅ΠΉ ΡΡΡΠ°Π½Ρ ΠΎΡΠ½ΠΎΡΠΈΡΠ΅Π»ΡΠ½ΠΎ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΠΌΠΈΡΠΎΠ²ΡΡ
Π»ΠΈΠ΄Π΅ΡΠΎΠ² ΠΏΠΎ ΡΠΈΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ. Π‘ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΡΠΈΡ Π΄Π°Π½Π° ΠΎΡΠ΅Π½ΠΊΠ° ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΠΉ Π²ΠΎΡΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π° Π½Π°ΡΠΎΠ΄ΠΎΠ½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ Π ΠΎΡΡΠΈΠΈ Π² ΠΊΠΎΠ½ΡΠ΅ΠΊΡΡΠ΅ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ³ΡΠΎΠ· ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π°. ΠΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ, ΠΎΡΡΠ°ΠΆΠ°ΡΡΠΈΠ΅ ΠΊΠ°ΠΊ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠ΅, ΡΠ°ΠΊ ΠΈ ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠ΅ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ° Π·Π°ΠΌΠ΅ΡΠ΅Π½ΠΈΡ ΡΠ΅Π»ΠΎΠ²Π΅ΡΠ΅ΡΠΊΠΈΡ
ΡΠ΅ΡΡΡΡΠΎΠ² ΡΡΡΠ°Π½Ρ, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ Π°Π±ΡΠΎΠ»ΡΡΠ½ΠΎΠΉ Π²Π΅Π»ΠΈΡΠΈΠ½Ρ ΠΈ ΠΈΠ½ΡΠ΅Π½ΡΠΈΠ²Π½ΠΎΡΡΠΈ Π΄Π΅ΡΠΎΡΠΎΠΆΠ΄Π΅Π½ΠΈΡ, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΊΠ°ΡΠ΅ΡΡΠ²Π° Π³Π΅Π½ΠΎΡΠΎΠ½Π΄Π° ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΈ. ΠΠ° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΡΠΌΠ΅ΡΡΠ½ΠΎΡΡΠΈ, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΡ
ΡΠΌΠ΅ΡΡΠ½ΠΎΡΡΡ ΠΎΡ Π²Π½Π΅ΡΠ½ΠΈΡ
ΠΏΡΠΈΡΠΈΠ½, Π²ΡΡΠ²Π»Π΅Π½Ρ ΡΠ΅ΠΊΡΡΠΈΠ΅ ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΠΈ Π΅ΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ Π²ΡΠ±ΡΡΠΈΡ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ
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