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Methods of optimizing data processing based on fuzzy correction of time series elements and variable identification models

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Kimyoviy texnologiya. Nazorat va boshqaruv

Kimyoviy texnologiya. Nazorat va boshqaruv

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The problem of optimal identification and processing of random time series (RTS) based on the use of the property of statistical, dynamic, fuzzy models is formulated. A method for the qualitative identification of RTS is proposed, including algorithms for fuzzy equations, logical conclusions, taking into account the effects of environmental factors and the nonstationarity of processes. A generalized algorithm for identifying the RTS with regulation and correction of variables values based on fuzzy logic rules, ways of searching for extrema by t norms and s-norms is developed. Designed tools for optimal data processing by determining the appropriate model; parametric and structural identification of objects; search optimization; learning models; identification of the dependence of "inputs and outputs"; formation and use of knowledge base, as well as sets of fuzzy rules, linguistic variables, membership functions and algorithms for regulating the values of variables. Methods of fuzzy correction of distorted information by means of the error control of RTS identification have been developed, and a software package has been implemented to providing high accuracy of data processing with significantly lower costs.

AUTHORS

I.Jumanov

Самаркандского филиала ТУИТ

Z.Bekmurodov

Самаркандского филиала ТУИТ

Tags

# оптималлаштириш# оптимизация# регулирование# optimization# regulation# программный комплекс# нестационарный объект# non-stationary object# software complex# ностационар объект# дастурий мажмуа# тасодифий вақтли қатор# нотиниқ тенглама# мантиқий хулосалаш# нотиниқ идентификациялаш# ростлаш# монанд модель# ўзгарувчилар қийматларини тўғрил# случайный временный ряд# нечеткие уравнения# логический вывод# нечеткая идентификация# адекватная модель# корректировка значений переменн# random time series# fuzzy equations# logical conclusion# fuzzy identification# adequate model# correction of variables values

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Article Identifiers

ROI:

https://eroi.uz/11.0008/A0120-0036

DOI:

Not Available

References

1. Barsegyan A. A., Kupriyanov M. S., Stepanenko V. V. Tehnologii analiza danny'h: Data Mining, Visual Mining, Text Mining, OLAP, SPb.: BHV- Peterburg, 2007. - 384 s. 2. Han j., Kamber M., Pei j. Data mining: concepts and techniques. - 3rd ed. - Morgan Kaufmann / Elsevier, 2012. - 744 p. 3. Jumanov I.I., SHarapova N.A. Sistema analiza i obrabotki danny'h o kadrah vuzov na osnove nechetkogo regulyatora s fiksirovannoy bazoy danny'h // «Himicheskaya tehnologiya. Kontrol' i upravlenie» - TGTU, Tashkent, 2014- № 2 (56) . - s. 53-61 4. Jumanov I.I. Sistema analiza i obrabotki danny'h o kolichestvenny'h i kachestvenny'h harakteristikah VUZa na osnove apparata myagkih vy'chisleniy // «Nauchny'y vestnik SamGU». - Samarқand: SamGU,2014 - №1 (83) - 35-42 b. 5. Djumanov O.I., Kholmonov S.M Methods and algorithms of selection the informative attributes in systems of adaptive data processing for analysis and forecasting // “Applied Technologies and Innovations”, Prague Development Center. - Prague, 2012. - Volume 8, November 2012. - pp.45-55. 6. Makary'chev P. P., Afonin A. YU. Operativny'y i intellektual'ny'y analiz danny'h. Penza, Izd-vo PGU, 2010. - 156 s. 7. Rotshteyn A. P. Intellektual'ny'e tehnologii identifikacii: nechetkaya logika, geneticheskie algoritmy', neyronny'e seti. - Vinnica, 1999.- 320 s. 8. Mityushkin YU. I., Mokin B. I., Rotshteyn A. P. Soft - Computing: identifikaciya zakonomernostey nechetkimi bazami znaniy. - Vinnica, 2002.- 145 s.