Simulation as a method of research of elements of innovative activity

Over the past years, special attention has been paid to the study of innovation. The innovative development path involves not only the development of new technologies and the release of high-tech products, but also the development of effective mechanisms for interaction among participants, the identification of priorities and tools for innovation policy, and the evaluation of the effectiveness and efficiency of innovation. Due to its relevance, the research work is aimed at expanding the capabilities of simulation modeling of innovative activities using the MATLAB interactive system. The result of the practical part of the study is the methodology for assessing the element of innovative activity, capable of taking into account potential influence factors that affect the effectiveness of the studied subject

Keywords: modeling of innovation, evaluation of innovation, MATLAB, fuzzy sets, fuzzy logic


  1. Big encyclopedia of oil and gas.
  2. L. S. Zvyagin. Actual economic and mathematical methods of studying modern economic processes//Problems of Economics and Management. 2015. № 2. P. 1-6.
  3. Dictionary of economic terms.
  4. O. I. Nikonov. Mathematical modeling and decision-making methods: textbook. Benefit. Yekaterinburg: Ural Publishing House. un-ta, 2015. 100 p.
  5. E. G. Azimov, A. N. Shchukin. New dictionary of methodological terms and concepts (theory and practice of teaching languages). Printed edition. M.: IKAR Publishing House, 2009.
  6. A. M. Novikov, D. A. Novikov. Methodology. M.: SIN-TEG, 2007. 668 p.
  7. D. A. Novikov, A. G. Chkhartishvili. Active forecast. Moscow: IPU RAN, 2002.
  8. V. A. Lucas. Theory of control of technical systems: Textbook. manual for universities. 4th edition, revised. Ekaterinburg: UGGU Publishing House, 2005. 677 p.
  9. I. V. Miroshnik, V. O. Nikiforov, A. L. Fradkov. Nonlinear and adaptive control of complex dynamic systems. SPb.: Nauka, 2000. 549 p.
  10. A. V. Panteleev. Control theory in examples and tasks: Textbook. Benefit. M.: Higher. shk., 2003. 583 p.
  11. V. N. Fomin, A. L. Fradkov, V. A. Yakubovich. Adaptive management of dynamic objects. M.: Science. Main edition of physical and mathematical literature, 1981. 448 p.
  12. S. G. Emelyanov, V. S. Titov, M. V. Bobyr. Intelligent systems based on fuzzy logic and soft arithmetic operations. Tutorial. M.: Argamak-Media, 2014. 341 p.
  13. V. A. Dykhta. Dynamical systems in economics. Introduction to the analysis of one-dimensional models. Tutorial. Irkutsk: BSUEP Publishing House, 2003. 178 p.
  14. K. V. Baldin. Risk management in the innovation and investment activities of the enterprise: Textbook. 2nd ed. M.: Publishing and trade corporation «Dashkov and K», 2012. 420 p.
  15. A. V. Tychinsky. Management of innovative activities of companies: modern approaches, algorithms, experience. Taganrog: TRTU, 2006. 189 p.
  16. A. I. Egorov. Foundations of control theory. M.: Fizmatlit, 2004. 504 p.
  17. S. D. Shtovba. Designing fuzzy systems by means. MATLAB. M.: Hotline - Tele-com, 2007.
  18. M. A. Gorkavy, A. I. Gorkavy. Intelligent systems in the tasks of managing technical and organizational-technological processes: textbook. allowance. Komsomolsk-on-Amur: FGBOU VO «KnAGTU», 2016. 117 p.
  19. A. V. Leonenkov. Fuzzy modeling in MATLAB and fuzzyTECH. SPb.: BHV-Petersburg, 2005.
  20. V. P. Dyakonov. VisSim + Mathcad + MATLAB. Visual mathematical modeling. M.: SOLON-Press, 2010. 384 p.
  21. D. B. Solovev, S. S. Kuzora. Fuzzy modeling of the assessment of a cluster element//Bulletin of the Nizhny Novgorod University n. a. N. I. Lobachevsky. Series: Social Sciences. 2019. № 2 (54). P. 23-28.
  22. D. B. Solovev, S. S. Kuzora, A. E. Merkusheva. A mathematical model for assessing the effectiveness of an innovation hub//Economics and Management: Problems, Solutions. 2018. Vol. 1. № 3. P. 3-10.
  23. D. B. Solovev, S. S. Kuzora, A. E. Merkusheva. The use of fuzzy inference algorithms for preliminary assessment of participants in the cluster approach//Innovations. 2018. № 5 (235). P. 77-81.
  24. D. B. Soloviev, S. S. Kuzora. Application of mathematical modeling in innovation//Creative Economy. 2019. Vol. 13. № 4. P. 701-712.
  25. D. B. Soloviev, I. P. Natarov, S. S. Kuzora. Modeling the assessment of the readiness of a constituent entity of the Russian Federation for innovation (by the example of Primorsky Krai)//Creative Economy. 2020. Vol. 14. № 5.
  26. D. B. Solovev, S. S. Kuzora. Methodology for assessing innovative activity through flexible algorithms//Innovations. 2019. № 6 (248). P. 78-87.
  27. D. B. Solovev, S. S. Kuzora. MATLAB for Simulation-Based Innovation Performance Assessment. 2019 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon). Vladivostok: Russia, 2019. P. 1-3.
  28. Central Bank of the Russian Federation.
  29. Official site of the Technopark «Russky».
  30. Electronic fund of legal and normative-technical documentation.