Chemical Technology, Control and Management


Solving decision-making problems in poorly formalized systems only with the help of deterministic and probabilistic methods is insufficient. To do this, it is necessary to widely apply the methods of hybrid intelligent systems and, especially, the methods of “soft” calculations (SoftCalculation, SoftComputing) and the directions of ComputationalIntelligence — intelligent computing technologies that are emerging on this theoretical and methodological base. An immune - fuzzy algorithm for the synthesis of fuzzy inference systems (FIS) is proposed. A two-stage adaptive FIS synthesis algorithm is described. At the first stage, the initial fuzzy parameters are clustered in order to reduce the number of input parameters of the fuzzy rules, and at the second stage, fuzzy models (inference rules) of the Sugeno type are synthesized.

First Page


Last Page



  1. Zade L.A. Ponyatie lingvisticheskoy peremennoy i ego primenenie k prinyatiyu priblijenny'h resheniy. - M.: Mir, 1976. -165 s.
  2. Aliev R.A., Aliev R.R. Teoriya intellektual'ny'h sistem i ee primenenie. - Baku, Izd-vo CHashy'ogly', 2001. - 720 s.
  3. SHtovba S.D. "Vvedenie v teoriyu nechetkih mnojestv i nechetkuyu logiku". http//www.matlab.exponenta.ru.
  4. Bekmuratov T,F., Muhamedieva D.T., Bobomuradov O.J. Model prediction of yield initial conditions. Ninth International Conference on Application of Fuzzy Systems and Soft Computing. ICAFS – 2010. . Edited by R.A. Aliev, K.W. Bonfig, M. Jamshidi, W. Pedrycz, I.B. Turksen. b – QuadratVerlag. Prague, Czech Republic. August 26-27, 2010. – pp. 321-328.
  5. Hopfield J.J., Tank D.W. “Neural” computation of decisions in optimization problems // Biological Cybernetics, 1985, vol. 52, no. 3, pp. 141-152.
  6. Hung D.L. Wang J. Digital hardware realization of a recurrent neural network for solving the assignment problem // Neurocomputing, 51, 2003, pp. 447-461.
  7. Holland J. H. Adaptation in natural and artificial systems. An introductory analysis with application to biology, control, and artificial intelligence.— London: Bradford book edition, 1994 —211 p.
  8. Bryant K., Benjamin A., Genetic Algorithms and the Traveling Salesman Problem, Department of Mathematics, HarveyMudd College, 2000.
  9. G.K., Mahotilo K.V., Petrashev S.N., Sergeev S.A., Geneticheskie algoritmy', iskusstvenny'e neyronny'e seti i problemy' virtual'noy real'nosti, Har'kov, OSNOVA, 1997. - 112s.
  10. Cantu-Paz E., Efficient and Accurate Parallel Genetic Algorithms, Lawrence Limermore National Lab, 2000.
  11. Dorigo Marco, Stutzle T. Ant colony optimization. – Cambridge: The MIT Press, 2004. – 305 p.
  12. Dasgupta D. Iskusstvenny'e immunny'e sistemy' i ih primenenie.- Fizmatlit.- 2006.-344 s.
  13. Dasgupta D., Artificial Immune Systems and Their Applications, Springer-Verlag, 1998.
  14. Muhamedieva D.T. Immunny'y algoritm resheniya zadach klassifikacii i prognozirovaniya v nechetkoy srede // Vestnik TUIT. Vy'p.1. -Tashkent. 2012. -S.38-41.
  15. Muxamediyeva D.T. Problems of constructing models of intellectual analysis of states of weakly formalizable processes // IOP Conf. Series: Journal of Physics: Conf. Series 1210 (2019) 012101 doi:10.1088/1742-6596/1210/1/012102
  16. Muxamediyeva D.T. Structure of fuzzy control module with neural network //International Journal of Mechanical and Production Engineering Research and Development (IJMPERD) ISSN (P): 2249-6890; ISSN (E): 2249-8001 Vol. 9, Issue 2, Apr 2019, pp.649-658 DOI : 10.24247/ijmperdapr201965.



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.