Automated system-cognitive analysis and the Eidos system as a method and toolkit for solving problems in various subject areas

In this paper, for the intelligent analysis of textual, numerical and graphical empirical data in various subject areas, a method of Automated system-cognitive analysis and its software tools — the intelligent Eidos system is proposed. A brief description of this method and tools is provided, which practically automate empirical cognition by many orders of magnitude increasing the possibilities of natural intelligence and are developed in a universal formulation, independent of the subject area and the specific task being solved. The specificity of this method is that independent and dependent variables can be formalized both in textual scales (logical, nominal (categorical linguistic variables) and ordinal) and in numerical scales in various units of measurement. At the same time, the method and tools ensure comparability of processing data of different types presented in different types of scales and in different units of measurement by metrizing text scales, i.e., increasing their degree of formalization to the level of numerical scales. This is achieved by calculating the amount of information or other quantitative measures of knowledge contained in the gradations of descriptive scales about the transition of the modeling object to the states described by the gradations of classification scales. The paper sets numerous tasks that can not only be solved using this method and tools, but are also stages of achieving the goal through Automated system-cognitive analysis of the modeling object. Task-1: cognitive structuring of the subject area, static and dynamic interpretation of classification and descriptive scales and gradations; Task-2: formalization of the subject area; Task-3: synthesis of statistical and system-cognitive models, multiparametric typing and particular criteria of knowledge; Task-4: verification of models; Task-5: selection of the most reliable model; Task-6: system identification and forecasting, integral criteria of knowledge; Task-7: decision support in simplified and developed versions; Task-8: the study of a modeling object by examining its model includes more than 10 subtasks.

1. Lutsenko E. V. Automated system-cognitive analysis in the management of active objects (systemic information theory and its application in the study of economic, socio-psychological, technological and organizational-technical systems). — Krasnodar: KubSAU, 2002. — 605 p. [in Russian]. EDN: OCZFHC

2. Orlov A. I., Lutsenko E. V. Systemic fuzzy interval mathematics. — Krasnodar: KubSAU, 2014. — 600 p. [in Russian]. EDN: RZJXZZ

3. Lutsenko E. V., Golovin N. S. Systems. — Krasnodar: VTsSKI «Eidos», 2024. — 518 p. [in Russian]. DOI: 10.13140/RG.2.2.22863.09123. EDN: INUTJL

4. Polythematic online electronic scientific journal of the Kuban State Agrarian University. http://ej.kubagro.ru/t2.asp?aut=11&keepThis=true&TB_iframe=true&width=750

5. Lutsenko E. V., Golovin N. S. Methodological principles of scientific knowledge and methods of presenting scientific results / KubSAU [in Russian]. DOI: 10.13140/rg.2.2.32569.79203. EDN: JQDIEX

6. Lutsenko E. V., Golovin N. S. The Revolution of the Early 21st Century in Artificial Intelligence: Deep Mechanisms and Prospects. — Krasnodar: KubSAU, 2024. — 495 p. [in Russian]. DOI: 10.13140/rg.2.2.17056.56321. EDN: OMIPIL

7. Lutsenko E. V. Synthesis of adaptive intelligent measuring systems using ASC analysis and the Eidos system, system identification in econometrics, biometrics, ecology, pedagogy, psychology and medicine / Scientific Journal KubSAU. 2016. No. 116. P. 1 – 60 [in Russian]. EDN: VQUVHJ

8. Shitikov V. K., Rosenberg G. S., Zinchenko T. D. Quantitative hydroecology: Methods of system identification. — Samara: Samara Scientific Center of the Russian Academy of Sciences, 2003. — 463 p. [in Russian]. ISBN 5-93424-109-5. EDN: QKMGTL

9. Orlov A. I. New paradigm of applied statistics / Industr. Lab. Mater. Diagn. 2012. Vol. 78. No. I-1. P. 87 – 93 [in Russia]. EDN: OOEMQT

10. Orlov A. I. Consistent criteria for testing absolute homogeneity of independent samples / Industr. Lab. Mater. Diagn. 2012. Vol. 78. No. 11. P. 66 – 70 [in Russian]. EDN: PIDWOR

11. Orlov A. I. Artificial intelligence, neural networks, big data and mathematical research methods / Industr. Lab. Mater. Diagn. 2023. Vol. 89. No. 7. P. 5 – 7 [in Russian]. DOI: 10.26896/1028-6861-2023-89-7-5-7. EDN: MYVPMI

12. Pokrovsky V. M., Abushkevich V. G., et al. Cardiorespiratory synchronism in the assessment of the regulatory and adaptive capabilities of the body. — Krasnodar: Kuban-book, 2010. — 243 p. [in Russian]. ISBN 978-5-91053-022-9. EDN: QLYKPD

13. Tsvetkov V. Ya. Knowledge extraction for the formation of information resources. — Moscow: State Research Institute of Information Educational Technologies, 2006. — 158 p. [in Russian]. EDN: RUYHKB

14. Polyakov A. A., Tsvetkov V. Ya. Applied informatics: A teaching aid. Vol. 2. — Moscow: «MAX Press», 2008. — 860 p. [in Russian]. EDN: RUXIHT

15. Blinkin M. Ya., Reshetova E. M. Road safety: History of the issue, international experience, basic institutions. — Moscow: Higher School of Economics, 2013. — 240 p. [in Russian]. EDN: VVQMFJ

16. Zakharova E. N. Study of weakly structured problems of socio-economic systems. Cognitive approach. — Rostov-on-Don: SFedU, 2006. — 332 p. [in Russian]. ISBN 5-7507-0220-0. EDN: RSGKOT

17. Orlov A. I. Mathematical methods of classification theory / Scientific Journal KubSAU. 2014. No. 95. P. 23 – 45 [in Russian]. EDN: RVEYCL

18. Rosenberg I. N., Tsvetkov V. Ya. Informatics and synergetics. — Moscow: MIIT, 2015. — 88 p. [in Russian]. EDN: TZAHWV

19. Savenok O. V. Optimization of the operation of operational equipment to improve the efficiency of oil field systems with complicated production conditions. — Krasnodar: ID «Yug», 2013. — 336 p. [in Russian]. EDN: TLSVJB

20. Martynushkin A. B. Formation of a risk management system for agricultural enterprises. Candidates Thesis. — Moscow, 2008. 177 p. [in Russian]. EDN: NQHTRH

21. Barmuta K. A., Bogdanova I. O., et al. Modern aspects of the formation of innovative economics and management. — Rostov-on-Don: Don State Technical University, 2020. — 159 p. [in Russian]. EDN: YEAAYS

22. Avrelkin V. A., Akulov A. V., et al. Quality of life in the 21st century: current problems and prospects. — Yekaterinburg: GC «Strategiya pozitiva», 2014. — 542 p. [in Russian]. EDN: TERCVV

23. Zelinskaya M. V., Pronin E. S. A systems approach to personnel selection: Main stages and criteria / Scientific Journal KubSAU. 2015. No. 108. P. 1093 – 1106 [in Russian]. EDN: TROMWP

24. Kotlyakov V. Yu. Methodology «System of Life Meanings» / Bulletin of Kemerovo State University. 2013. No. 2-1(54). P. 148 – 153 [in Russian]. EDN: QBFAVV

25. Kozlova O. A., Gladkova T. V., et al. Methodological approach to measuring the quality of life of the regional population / Regional Economy. 2015. No. 2(42). P. 182 – 193 [in Russian]. DOI: 10.17059/2015-2-15. EDN: VHRTJL

26. Poya D. Mathematics and plausible reasoning. — Moscow: Nauka, 1975. — 464 p. [in Russian].

27. Makarenko S. I. Intelligent information systems: A tutorial. — Stavropol, 2009. — 206 p. [in Russian]. EDN: QIRWSN

28. Bortalevich S. I., Loginov E. L., et al. Strategic management of distributed objects in conditions of self-organized criticality of the external environment. — Moscow: Institute of Market Problems of the Russian Academy of Sciences, 2015. — 202 p. [in Russian]. EDN: TCESIN

29. Lyantsev A. V., Starodubtsev M. P. Information technology as an integral part of training in the education system / Actual problems of professional and applied physical culture and sports: Interuniversity collection of scientific and methodological works. — St. Petersburg: Politekh-Press, 2020. P. 17 – 21 [in Russian]. EDN: TSWCCT

30. Karpun N. N. The structure of complexes of harmful organisms of woody plants in the humid subtropics of Russia and biological justification of protection measures. Doctoral thesis. — Sochi, 2018. — 399 p. [in Russian]. EDN: ZOSTYA

31. Rakov D. L. Structural analysis and synthesis of new technical systems based on the morphological approach. — Moscow: Knizhny Dom «LIBROKOM», 2011. — 159 p. [in Russian]. ISBN 978-5-397-02604-8. EDN: QMHIVZ

32. Safronova T. I. Information model for managing the quality of the rice irrigation system / Proceedings of KubSAU. 2007. No. 6. P. 11 – 15 [in Russian]. EDN: JUGWXJ

33. Bogatkina Yu. G. et al. Application of information technologies for economic evaluation of oil and gas investment projects. — Moscow: «MAX Press», 2016. — 148 p. [in Russian]. ISBN 978-5-317-05187-7. EDN: VJVGIJ

34. Lutsenko E. V., Loiko V. I., et al. Systems of knowledge representation and acquisition. — Krasnodar: Ékoinvest, 2018. — 513 p. [in Russian]. EDN: UZZBLC

35. Ermolenko V. V. Intellectual human capital in ensuring the adoption of unique management decisions in a corporation. Theory, methodology and tools. — Krasnodar: KubSU, 2012. — 363 p. [in Russian]. ISBN 978-5-8209-0798-2. EDN: RAIEPZ

36. Mekhrentsev A. V., Khrushcheva M. I., et al. Quality of life: Problems and prospects of the 21st century: Collective monograph. — Yekaterinburg: GC «Positive Strategy», 2013. — 532 p. [in Russian]. ISBN 978-5-94984-389-5. EDN: QCEIAT

37. Abduzhalilov Kh. A., Avanesyan K. A., et al. Ecosystems in the space of the new economy. — Rostov-on-Don: SFedU, 2020. — 788 p. [in Russian]. ISBN 978-5-9275-3706-8. EDN: VCAFTP

38. Nasyrova S. I. Human-Centered Economy: Definition Development / Russian Journal of Economics and Law. 2022. Vol. 16. No. 2. P. 258 – 274 [in Russian]. DOI: 10.21202/2782-2923.2022.2.258-274. EDN: SDXTAR

39. Reks L. M., Umyvakin V. M., et al. Mathematical model of the ecological situation in the rice irrigation system / Scientific Journal KubSAU. 2008. No. 44. P. 191 – 208 [in Russian]. EDN: JWXXYN

40. Akhremenko A. S., Yevtushenko S. A. Quality of life in the regions of Russia: Political science aspect, methodology and measurement techniques / Bulletin of Moscow University. Series 12: Political Sciences. 2010. No. 1. P. 67 – 83 [in Russian]. EDN: LLSYYB

41. Khlopova T. P., Romanova M. L., et al. Monitoring the quality of education in modern conditions. — Krasnodar: KubSTU, 2013. — 166 p. [in Russian]. ISBN 978-5-8333-0471-6. EDN: ROKNSH