System diagnostics socio-economic processes
Macrosystem dynamics
Methods of decision making
V.A. Marenko Technologies for Decisions Problems of System Analysis Using a Cognitive Fpproach
Applied aspects in informatics
System analysis in medicine and biology
V.A. Marenko Technologies for Decisions Problems of System Analysis Using a Cognitive Fpproach
Abstract. 

The purpose of the article is to describe the technology by the example of the functioning of the economic system according to the factors “competitiveness”, “profit”, “customer loyalty” and “state” of the economy. The technology is implemented in three stages. At each stage, cognitive models are formed with varying degrees of detail. At the first stage, the first cognitive model is built in the form of a digraph. Vertices consist of factors and the relationships between them are taken into account. At this stage, the subsystems of the cognitive model are identified. At the second stage, a second cognitive model is formed in the form of a generalized digraph. Vertices consist of subsystems of the first cognitive model. With the second cognitive model, a simulation experiment is conducted to identify the subsystem most sensitive to impulse action. At the third stage, a third cognitive model is constructed in the form of a detailed digraph. Vertices are formed from detailed subsystems of the first cognitive model. Causal relationships are represented by the weights of arcs. With the third cognitive model, a simplicial analysis for and a simulation experiment are carried out. Based on the results of simulation experiments, a set of graphic materials was formed. It is used to select a variant of the system for the purpose of practical implementation.

Keywords: 

cognitive model, digraph, simulation experiment, economic system

PP. 52-63.

DOI: 10.14357/20790279220206
 
References

1. Kapustina L.G. Metodika sistemnogo analiza i otsenki effektivnosti primeneniya informatsionno-kommunikatsionnykh tekhnologiy // Metodist. 2017. No 5. P. 63-67.
2. Bondarenko I.S. Klassifikatsiya, kak metod sistemnogo analiza, v probleme vybora tekhnologii stroitel’stva // Gornyy informatsionno-analiticheskiy byulleten’. 2008. No 510. P. 130-135.
3. Yakovlev O.V. Formirovaniye metodologii sistemnogo analiza bezopasnosti novykh naukoyemkikh tekhnologiy // Strategicheskaya stabil’nost’. 2011. No 4 (57). P. 73-75.
4. Belousova N.I., Vasil’yeva Ye.M., Livshits V.N., Mironova I.A. Kontseptual’nyye osnovy modelirovaniya otsenki sistemnoy effektivnosti razvitiya transportnoy infrastruktury // Trudy Instituta sistemnogo analiza Rossiyskoy akademii nauk. 2021. T. 71. No 1. P. 10-21
5. Kocherzhinskaya Yu.V. and others. Usage of System Analysis methods in the software products engineering. J. of Engineering and Applied Sciences. 2018. Vol. 13. No 9. P. 3294-3298.
6. Dasgupta S. and others. User Acceptance of CASE Tools in Systems Analysis and Design: An Empirical Study. J. of Informatics Education Research. 2007. Vol. 9. No 1. P. 51-77.
7. Kezhayev V.A., Chubasov V.A. Metodika sistemnogo analiza adaptivnogo upravleniya tekhnicheskim sostoyaniyem raketno-artilleriyskogo vooruzheniya // Izvestiya Rossiyskoy akademii raketnykh i artilleriyskikh nauk. 2018. No 1 (101). P. 87-93.
8. Pospelov, D.A. Situatsionnoye upravleniye. Teoriya i praktika. M.: Nauka. Gl. red. fizyu-mat. lit. 1986. 288 p.
9. Sorokoletov P.V. Analiz, problemy i sostoyaniye modeley predstavleniya znaniy v sistemakh prinyatiya resheniy // Perspektivnyye informatsionnyye tekhnologii i intellektual’nyye sistemy. 2006. No 4. P. 16-24.
10. Pospelov D.A. Prikladnaya semiotika i iskusstvennyy intellekt // Programmnyye produkty i sistemy. 1996. No 3. P. 10-13.
11. Baryshev M.V., Gatchin I.YU., Gatchin YU.A. Modeli predstavleniya znaniy ekspertnykh sistem // Nauchno-tekhnicheskiy vestnik Sankt-Peterburgskogo gosudarstvennogo universiteta informatsionnykh tekhnologiy, mekhaniki i optiki. 2006. No 29. P. 14-18.
12. Pospelov D.A. Znaniya v intellektual’nykh sistemakh // Programmnyye produkty i sistemy. 1990. No 3. P. 67-79.
13. Belous Ye.S., Kudinov V.A., Zhelnin M.E. Sovremennyye modeli predstavleniya znaniy v obuchayushchikh sistemakh // Uchenyye zapiski. Elektronnyy nauchnyy zhurnal Kurskogo gosudarstvennogo universiteta. 2010. No 1 (13). P. 9-14.
14. Yeliseyev D.V. Model’ predstavleniya znaniy pri sozdanii adaptivnoy informatsionnoy sistemy // Nauka i obrazovaniye: nauchnoye izdaniyeMGTU im. N.E. Baumana. 2010. No 3. 2 p.
15. Zagorul’ko YU.A. O kontseptsii integrirovannoy modeli predstavleniya znaniy // Izvestiya Tomskogo politekhnicheskogo universiteta. 2013. T. 322. No 5. P. 98-103.
16. Borisov V.V., Zernov M.M. Realizatsiya situatsionnogo podkhoda na osnove nechetkoy iyerarkhicheskoy situatsionno-sobytiynoy seti // Iskusstvennyy intellekt i prinyatiye resheniy. 2009. No 1. P. 17-30.
17. Pospelov D.A. Desyat’ «goryachikh tochek» v issledovaniyakh po iskusstvennomu intellektu // Intellektual’nyye sistemy (MGU). 1996. T. 1. Vyp. 1-4. P. 47-56.
18. Taler R. Novaya povedencheskaya ekonomika. Pochemu lyudi narushayut pravila traditsionnoy ekonomiki i kak na etom zarabotat’. M.: Eksmo. 2017. 368 p.
19. Saymon G. Nauki ob iskusstvennom. M.: Yeditorial URSS. 2004. 144 p.
20. Shastitko A.A. Povedencheskaya ekonomika: primeneniye metodov kognitivnoy psikhologii v ekonomike // Obshchestvennyye nauki i sovremennost’. 2017. No 2. P. 132-141.
21. Kaneman D., Slovik P., Tverski A. Prinyatiye resheniy v neopredelennosti: pravila i predubezhdeniya. Khar’kov: Gumanitarnyy tsentr. 2005. 632 p.
22. Alekseycheva Ye.YU., Shinkareva O.V. Sovremennyye tendentsii razvitiya global’noy ekonomiki v kontekste issledovaniy povedencheskoy ekonomiki // Vestnik Yekaterininskogo instituta. 2019. No 4 (48). P. 4-11.
23. Vol’chik V.V. Povedencheskaya ekonomika i sovremennyye tendentsii evolyutsii instituta sobstvennosti // Terra Economicus. 2010. Vol. 8. No 2. P. 71-78.
24. Nikonova T.V., Shushakova A.A., Kodolova I.A. Sovremennyye tendentsii i faktory sberegatel’nogo povedeniya naseleniya v rossiyskoy ekonomike // Uchet i statistika. 2020. No 3 (59). P. 95-105.
25. Ak’yulov R.I. Sovremennyye tendentsii razvitiya tenevoy zanyatosti v rossiyskoy ekonomike // Diskussiya. 2020. No 2 (99). P. 50-57.
26. Avdeyeva Z.K., Kovriga S.V. Podkhod k postanovke zadachi upravleniya na kognitivnoy modeli situatsii dlya strategicheskogo monitoringa / V sb. Upravleniye bol’shimi sistemami. M. : IPU RAN. 2016. Vol. 59. P. 120–146.
27. Saymon G.A. Teoriya prinyatiya resheniy v ekonomicheskoy teorii i nauke o povedenii / V kn. Vekhi ekonomicheskoy mysli T.2. Teoriya firmy / Pod red. V.M. Gal’perina – SPb.: Ekonomicheskaya shkola. 2000. P. 54-72.
28. Lozhnikov V., Marenko V. Software for the computational experiment “Synthesis of the topological structure of the cognitive model”. 2020. J. Phys.: Conf. Ser. 1441 012148.
29. Roberts F.S. Discrete Mathematical Models, with Applications to Social, Biological and Environmental Problems, Prentice-Hall, Englewood Cliffs, NJ. 1976.
30. Marenko V.A., Mil’charek T.P., Mil’charek N.A. Diagnostika i modelirovaniye ekstremistskoy napravlennosti lichnosti // Trudy ISA RAN. 2021. T. 71. No 3. P. 21-32.
 

2023-73-4
2023-73-3
2023-73-2
2023-73-1

© ФИЦ ИУ РАН 2008-2018. Создание сайта "РосИнтернет технологии".