tuzsutТруды учебных заведений связиProceedings of Telecommunication Universities1813-324X2712-8830СПбГУТ10.31854/1813-324X-2020-6-3-58-65tuzsut-132Research ArticleИНФОРМАТИКА, ВЫЧИСЛИТЕЛЬНАЯ ТЕХНИКА И УПРАВЛЕНИЕINFORMATICS, COMPUTER ENGINEERING AND MANAGEMENTМетод валидации графовых моделей на основе алгоритма эффективных управленийMethod for Validating Graph Models Based on the Effective Control AlgorithmВасильевВ. С.VasilievV. ..noemail@neicon.ruЦелыхА. Н.TselykhA. ..ant@sfedu.ruЦелыхЛ. А.TselykhL. ..noemail@neicon.ruИнститут компьютерных технологий и информационной безопасности Южного федерального университетаРоссияInstitute of Computer Technologies and Information Safety of Southern Federal UniversitRussian FederationТаганрогский институт имени А.П. Чехова (филиал) Ростовского государственного экономического университетаРоссияTaganrog Institute named after A.P. Chekhov (branch) of Rostov State University of EconomicsRussian Federation202013042021635865Copyright © Васильев В.С., Целых А.Н., Целых Л.А., 20212021Васильев В.С., Целых А.Н., Целых Л.А.Vasiliev V..., Tselykh A..., Tselykh L...This work is licensed under a Creative Commons Attribution 4.0 License.https://tuzs.sut.ru/jour/article/view/132

В статье предлагается метод валидации математических моделей, представленных ориентированными взвешенными знаковыми графами, с использованием алгоритма эффективных управлений. Метод рассматривает валидируемую модель с точки зрения спектральных свойств матрицы смежности графа, представленного нечеткой когнитивной картой (НКК). Использование алгоритма эффективных управлений позволяет определить направленность собственного вектора матрицы смежности. Это свойство определяет критерии проверки НКК.

The article proposes a method for validating mathematical models represented by oriented weighted signed graphs using an efficient control algorithm. The method considers the validated model in terms of spectral properties of the graph adjacency matrix represented by a fuzzy cognitive map (FCM). Using an efficient control algorithm, you can determine the eigenvector direction of the adjacency matrix. This property defines the criteria for checking the FCM.

валидация моделейнаправленный взвешенный графнечеткая когнитивная картаэффективное управлениеmodel validationdirected weighted graphfuzzy cognitive mapefficient managementReferencesKosko B. Fuzzy cognitive maps // International Journal of Man-Machine Studies. 1986. Vol. 24. Iss. 1. PP. 65-75. DOI:10.1016/S0020-7373(86)80040-2Kosko B. Fuzzy cognitive maps // International Journal of Man-Machine Studies. 1986. Vol. 24. Iss. 1. PP. 65-75. DOI:10.1016/S0020-7373(86)80040-2Salmeron J.L., Mansouri T., Moghadam M.R.S., Mardani A. Learning Fuzzy Cognitive Maps with modified asexual reproduction optimisation algorithm // Knowledge-Based Systems. 2019. Vol. 163. PP. 723-735. DOI:10.1016/j.knosys.2018.09.034Salmeron J.L., Mansouri T., Moghadam M.R.S., Mardani A. Learning Fuzzy Cognitive Maps with modified asexual reproduction optimisation algorithm // Knowledge-Based Systems. 2019. Vol. 163. PP. 723-735. 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The authors declare that there are no conflicts of interest present.