Methodology to determine the probalistic demand of mass attraction centers based on the classification within the framework of macrosystems theory
https://doi.org/10.26518/2071-7296-2022-19-1-62-73
Abstract
Introduction. The calculation of correspondence was described at the beginning of the 20 century in the form of a gravitational model and is based on analogy with the law of universal gravitation. The development of this model can be called J. Wilson’s approach, in which correspondence calculations are performed using an entropy model. The entropy approach operates with various expressions for the entropy of a macroscopic system. At the same time, its equilibrium is achieved at the maximum value of the selected entropy function. The purpose of this work is to develop a methodology for determining the probabilistic demand of mass attraction centers - Shopping centers and to demonstrate the results of its application on the example of shopping centers located on the territory of the city of Tula. Probabilistic demand is necessary to obtain the so-called ‘a priori probabilities’ in the expression of the entropy of the transport macrosystem.
Methods and Materials. For the development of the methodology, as well as its further use, the most convenient and promising scientific platform is the theory of transport macrosystems, which is a special case of the general theory of macrosystems. Developed in the works of mainly domestic scientists, it allows you to perform various tasks specific to transport systems.
Conclusions. The method of determining the probabilistic demand of the mass attraction centers -Shopping centers, which consists in obtaining a priori probabilities of being in them and their capacities for solving problems of finding equilibrium distributions of visitors, was developed with the aim of further developing the macroscopic approach in the study of Shopping centers. The main purpose of the technique is to use the results obtained in solving problems about the equilibrium states of the drains of transport and the road network in the framework of the theory of transport macrosystems.
About the Authors
I. E. AgureevRussian Federation
Igor E. Agureev – Dr of Sci., Associate Professor
Tula
G. E. Pyshnaya
Russian Federation
Galina E. Pyshnaya – Undergraduate
Tula
V. A. Pyshnyi
Russian Federation
Vladislav A. Pyshnyi – Cand. of Sci., Associate Professor
Tula
References
1. Carrothers G. A. P. An historical review of the gravity and potential concepts of human interaction // J. American Instit. Planners. 1956. 22: 94-102.
2. Modelirovanie transportnyh potokov v krupnom gorode s primeneniem k moskovskoj aglomeracii / A. S. Aliev, A. I. Strel’nikov, V. I. Shvecov, Ju. Z. Shershevskij // Avtomatika i telemehanika. 2005. 11: 113–125. (In Russian)
3. Gasnikov A. V., Gasnikova E. V. O vozmozhnoj dinamike v modeli raschjota matricy korrespondencij (A. Dzh. Vil’sona) // TRUDY MFTI. 2010. 2(4): 45 –54. (In Russian)
4. Agureev I. E. Nelinejnye modeli transportnyh sistem // Mir transporta i tehnologicheskih mashin. Orel: GTU. 2009. 2: 3–16. (In Russian)
5. Burkov D. G., Zedgenizov A. V. Matematicheskoe opisanie transportnogo sprosa k ob#ektam kul’turnobytovoj napravlennosti // Vestnik IrGTU. 2016. 20(12): 201–209. (In Russian)
6. Zhankaziev S. V. Metodologicheskie principy postroenija telematicheskoj sistemy kosvennogo upravlenija transportnymi potokami // Vestnik Moskovskogo avtomobil’no- dorozhnogo gosudarstvennogo tehnicheskogo universiteta (MADI). 2010. 3: 48 –54. (In Russian)
7. Miroshnichenko D.I. Analiz kriteriev konkurentosposobnosti torgovyh centrov // Nauchnyj vestnik Volgogradskogo filiala RANHiGS. Serija: Jekonomika. 2015. 3: 76–81. (In Russian)
8. Marketingovoe issledovanie po ocenke torgovyh centrov g. Kazani https://studbooks.net/779159/marketing/marketingovoe_issledovanie_po_otsenke_torgovyh_tsentrov_g_kazani.
9. Struktura kompleksnoj modeli transportnoj sistemy g. Moskvy / A.S. Aliev, D.S. Mazurin, D. A. Maksimova, V.I. Shvecov // Trudy ISA RAN. 2015. 65(1): 3–15. (In Russian)
10. Shvecov V. I. Problemy modelirovanija peredvizhenij v transportnyh setjah // TRUDY MFTI. 2010. 2(4): 169–179. (In Russian)
11. Piovani D, Arcaute E, Uchoa G, Wilson A, Batty M. 2018 Measuring accessibility using gravity and radiation models. R. Soc. open sci. 5: 171668. http://dx.doi.org/10.1098/rsos.171668.
12. Indriany S., Sjafruddin A., Kusumawati A., et al. Mode choice model for working trip under risk and uncertainty. AIP Conference Proceedings 1977, 020041 (2018); https://doi.org/10.1063/1.5042897 Published Online: 26 June 2018.
13. Wan L., Jin Y. Assessment of model validation outcomes of a new recursive spatial equilibrium model for the Greater Beijin/ September 2017. Environment and Planning B Urban Analytics and City Science 46(2): 239980831773257. DOI:10.1177/2399808317732575.
14. Chmielewski J., Kempa J. Hexagonal Zones in Transport Demand Models. In International Congress on Engineering. Engineering for Evolution, KnE Engineering, pages 103–116. DOI 10.18502/keg.v5i6.7025.
15. Fox J., Patruni B. South East Wales Transport Model. Demand Model Implementation. Santa Monica, CA: RAND Corporation, 2018. https://www.rand.org/pubs/research_reports/RR1927z3.html.
16. Miller E. J. Accessibility: measurement and application in transportation planning, Transport Reviews, 38:5, 551-555, DOI: 10.1080/01441647.2018.1492778.
17. Klinkhardt C., Woerle T., Briem L., et al. Using OpenStreetMap as a Data Source for Attractiveness in Travel Demand Models. Transportation Research Record 2021, Vol. 2675(8) 294–303.
18. Suprayitno H. Developing a direct gravity trip distribution model for air passenger demand. 2020 IOP Conf. Ser.: Earth Environ. Sci. 419 012092.
19. Naser I. H., Mahdi M. B., Meqtoof F. H., et al. Modelling Trip Distribution Using the Gravity Model and Fratar’s Method. Mathematical Modelling of Engineering Problems 2021, 8(2): 230-236. DOI: https://doi.org/10.18280/mmep.080209.
20. Waldrip S. H., Niven R. K., Abel M. et al. Maximum Entropy Analysis of Transport Networks. BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: Proceedings of the 36th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2016). DOI:10.1063/1.4985364.
Review
For citations:
Agureev I.E., Pyshnaya G.E., Pyshnyi V.A. Methodology to determine the probalistic demand of mass attraction centers based on the classification within the framework of macrosystems theory. The Russian Automobile and Highway Industry Journal. 2022;19(1):62-73. (In Russ.) https://doi.org/10.26518/2071-7296-2022-19-1-62-73