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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">umovest</journal-id><journal-title-group><journal-title xml:lang="ru">Статистика и Экономика</journal-title><trans-title-group xml:lang="en"><trans-title>Statistics and Economics</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2500-3925</issn><publisher><publisher-name>Plekhanov Russian University of Economics</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.21686/2500-3925-2022-4-71-86</article-id><article-id custom-type="elpub" pub-id-type="custom">umovest-1642</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>СТАТИСТИКА И МАТЕМАТИЧЕСКИЕ МЕТОДЫ В ЭКОНОМИКЕ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>STATISTICAL AND MATHEMATICAL METHODS  IN ECONOMICS</subject></subj-group></article-categories><title-group><article-title>Методический аппарат когнитивного моделирования социально-экономической системы (университета)</article-title><trans-title-group xml:lang="en"><trans-title>Methodological Apparatus of Cognitive Modeling of Socio-Economic System (University)</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Микрюков</surname><given-names>А. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Mikryukov</surname><given-names>A. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Андрей Александрович Микрюков - к.т.н., доцент</p><p>Москва</p></bio><bio xml:lang="en"><p>Andrey A. Mikryukov - Cand. Sci. (Engineering), Associate Professor</p><p>Moscow</p></bio><email xlink:type="simple">mikrukov.aa@rea.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Мазуров</surname><given-names>М. Е.</given-names></name><name name-style="western" xml:lang="en"><surname>Mazurov</surname><given-names>M. E.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Михаил Ефимович Мазуров - д.ф.-м.н., профессор</p><p>Москва</p></bio><bio xml:lang="en"><p>Mikhail E. Mazurov - Dr. Sci. (Physics and Mathematics), Professor</p><p>Moscow</p></bio><email xlink:type="simple">Mazurov37@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Российский экономический университет им. Г. В. Плеханова</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Plekhanov Russian University of Economics</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2022</year></pub-date><pub-date pub-type="epub"><day>22</day><month>08</month><year>2022</year></pub-date><volume>19</volume><issue>4</issue><fpage>71</fpage><lpage>86</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Микрюков А.А., Мазуров М.Е., 2022</copyright-statement><copyright-year>2022</copyright-year><copyright-holder xml:lang="ru">Микрюков А.А., Мазуров М.Е.</copyright-holder><copyright-holder xml:lang="en">Mikryukov A.A., Mazurov M.E.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://statecon.rea.ru/jour/article/view/1642">https://statecon.rea.ru/jour/article/view/1642</self-uri><abstract><sec><title>Цель исследования</title><p>Цель исследования. Целью исследования является совершенствование методического аппарата когнитивного моделирования социально-экономических систем (СЭС) и прогнозирования показателей их функционирования и развития, обеспечивающего повышение точности и достоверности получаемых результатов. Существующие модели и методики не в полной мере обеспечивают необходимую точность и достоверность моделей, что требует развития математического аппарата когнитивного моделирования в части повышения качества разрабатываемых когнитивных моделей.</p></sec><sec><title>Материалы и методы</title><p>Материалы и методы. Для достижения поставленной цели использованы методы комплексного подхода к решению поставленной задачи, декомпозиции ее на взаимосвязанные этапы, описание содержания каждого этапа в их взаимосвязи и представление обобщенного варианта методики с учетом особенностей объекта исследования. Разработанный подход обеспечивает построение более точной и достоверной когнитивной модели. Показана эффективность разработанного методического аппарата.</p></sec><sec><title>Результаты</title><p>Результаты. Проведен детальный анализ существующих критериев и подходов к решению задачи верификации когнитивных моделей, который показал отсутствие единой методики и комплексного подхода в решении задач когнитивного моделирования СЭС на основе когнитивных карт. Разработана совокупность методик, реализующих этапы когнитивного моделирования: методика построения проблемного поля ситуации; методика синтеза когнитивной карты, ее структурно-целевого анализа и анализа системных характеристик, а также методика верификации когнитивной модели.</p></sec><sec><title>Заключение</title><p>Заключение. Предложено комплексное решение задачи построения когнитивной модели анализа и прогнозирования деятельности университета, включающее совокупность этапов: этап построения проблемного поля ситуации; идентификации факторов и связей между ними; этапе построения когнитивной карты и ее верификации, а также этап анализа системных характеристик когнитивной модели, валидации когнитивной модели. Разработанный методический аппарат предназначен для получения адекватной модели, обеспечивающей более точные и достоверные результаты моделирования объекта исследования.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Purpose of the study</title><p>Purpose of the study. The aim of the study is to improve the methodological apparatus of cognitive modeling of socio-economic systems (SES) and predicting the indicators of their functioning and development, which ensures an increase in the accuracy and reliability of the results obtained. Existing models and methods do not fully provide the necessary accuracy and reliability of models that requires the development of the mathematical apparatus of cognitive modeling in terms of improving the quality of the developed cognitive models.</p></sec><sec><title>Materials and methods</title><p>Materials and methods. To achieve this goal, methods of an integrated approach to solving the problem, decomposing it into interrelated stages, describing the content of each stage in their relationship and presenting a generalized version of the methodology, taking into account the characteristics of the object of study, were used. The developed approach provides creating a more accurate and reliable cognitive model. The effectiveness of the developed methodological apparatus is shown.</p></sec><sec><title>Results</title><p>Results. A detailed analysis of the existing criteria and approaches to solving the problem of verification of cognitive models was carried out, which showed the absence of a unified methodology and an integrated approach in solving problems of cognitive modeling of SES based on cognitive maps. A set of techniques that implement the stages of cognitive modeling has been developed. The results of a comparative analysis of the developed approach with the existing ones are presented.</p></sec><sec><title>Conclusion</title><p>Conclusion. A comprehensive solution to the problem of creating a cognitive model for analyzing and predicting the activities of a university is proposed, which includes a set of stages: the stage of creating the problem field of the situation; identification of factors and relationships between them; the stage of making a cognitive map and its verification, as well as the stage of analyzing the system characteristics of the cognitive model, validating the cognitive model. The developed methodological apparatus includes a set of techniques aimed at obtaining an adequate model that provides more accurate and reliable results of modeling the object of study.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>нечеткое когнитивное моделирование</kwd><kwd>сценарное прогнозирование</kwd><kwd>когнитивная карта</kwd><kwd>методический аппарат</kwd></kwd-group><kwd-group xml:lang="en"><kwd>fuzzy cognitive modeling</kwd><kwd>scenario forecasting</kwd><kwd>cognitive map</kwd><kwd>methodological apparatus</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Работа выполнена при финансовой поддержке ФГБОУ ВО «РЭУ им. Г. В. Плеханова».</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Авдеева З.К, Коврига С.В., Макаренко Д.И., Максимов В.И. Когнитивный подход в управлении // Проблемы управления. 2007. № 3. С. 2–8.</mixed-citation><mixed-citation xml:lang="en">Avdeyeva Z.K, Kovriga S.V., Makarenko D.I., Maksimov V.I. Cognitive approach in management. Problemy upravleniya = Problems of management. 2007; 3: 2–8. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Авдеева З. К., Коврига С. В. Подход к постановке задач управления на когнитивной модели ситуации для стратегического мониторинга // Управление большими системами. 2016. № 5. С. 120–146.</mixed-citation><mixed-citation xml:lang="en">Avdeyeva Z. K., Kovriga S. V. Approach to the formulation of control problems on the cognitive model of the situation for strategic monitoring. Upravleniye bolʹshimi sistemami = Management of large systems. 2016; 5: 120-146. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Пылькин А.Н., Крошилин А.В., Крошилина С.В. Проектирование систем поддержки принятия решений для оценки состояния здоровья пациентов в условиях неопределенности // Информатика и системы управления. 2010. № 4(26). C. 82–94.</mixed-citation><mixed-citation xml:lang="en">Pylʹkin A.N., Kroshilin A.V., Kroshilina S.V. Designing decision support systems for assessing the health status of patients under uncertainty. Informatika i sistemy upravleniya = Informatics and control systems. 2010; 4(26): 82-94. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Федулов А.С. Нечеткие реляционные когнитивные карты // Известия РАН. Теория и системы управления. 2005. № 1. С. 120–132.</mixed-citation><mixed-citation xml:lang="en">Fedulov A.S. Fuzzy relational cognitive maps. Izvestiya RAN. Teoriya i sistemy upravleniya = Bulletin of the Russian Academy of Sciences. Theory and control systems. 2005; 1: 120–132. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Hajeck P., Prochazka O. Interval-Valued Fuzzy Cognitive Maps for Supporting Business Decisions // In Proceedings of IEEE International Conference on Fuzzy Systems. Vancouver, BC, Canada. 2016. С. 531–536.</mixed-citation><mixed-citation xml:lang="en">Hajeck P., Prochazka O. Interval-Valued Fuzzy Cognitive Maps for Supporting Business Decisions. In Proceedings of IEEE International Conference on Fuzzy Systems. Vancouver, BC, Canada. 2016: 531–536.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Salmeron J.L. Modelling Grey Uncertainty with Fuzzy Grey Cognitive Maps // Expert Systems with Applications. 2010. Т. 37. № 12. С. 7581–7588.</mixed-citation><mixed-citation xml:lang="en">Salmeron J.L. Modelling Grey Uncertainty with Fuzzy Grey Cognitive Maps. Expert Systems with Applications. 2010; 37; 12: 7581–7588.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Espinosa M.L., Depaire B., Vanhoof K. Fuzzy Cognitive Maps with Rough Concepts // Proc. of the 9th Intern. Conf. on Artificial Intelligence Applications and Innovations (AIAI’2013). Paphos, Greece. 2013. С. 527–536.</mixed-citation><mixed-citation xml:lang="en">Espinosa M.L., Depaire B., Vanhoof K. Fuzzy Cognitive Maps with Rough Concepts. Proc. of the 9th Intern. Conf. on Artificial Intelligence Applications and Innovations (AIAI’2013). Paphos, Greece. 2013: 527–536.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Papageorgiou E.I., Iakovidis D.K. Intuitionistic Fuzzy Cognitive Maps // IEEE Trans. on Fuzzy Systems. 2013. Т. 21. № 2. С. 342–354.</mixed-citation><mixed-citation xml:lang="en">Papageorgiou E.I., Iakovidis D.K. Intuitionistic Fuzzy Cognitive Maps. IEEE Trans. on Fuzzy Systems. 2013; 21; 2: 342 - 354.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Carvalho J.P., Tome J.A.B. Rule Based Fuzzy Cognitive Maps: Fuzzy Causal Relations. In: Computational Intelligence for Modeling, Control and Automation: Evolutionary Computation &amp; Fuzzy Logic for Intelligent Control, Knowledge Acquisition &amp; Information Retrieval / Edited by M. Mohammadian, IOS Press. 1999.</mixed-citation><mixed-citation xml:lang="en">Carvalho J.P., Tome J.A.B. Rule Based Fuzzy Cognitive Maps: Fuzzy Causal Relations. In: Computational Intelligence for Modeling, Control and Automation: Evolutionary Computation &amp; Fuzzy Logic for Intelligent Control, Knowledge Acquisition &amp; Information Retrieval / Ed. by M. Mohammadian, IOS Press. 1999.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Miao Y., Liu Z.-Q., Siew Ch.Y. Dynamical Cognitive Network – an Extension of Fuzzy Cognitive Map // IEEE Trans. on Fuzzy Systems. 2001. Т. 9. № 5. С. 760–770.</mixed-citation><mixed-citation xml:lang="en">Miao Y., Liu Z.-Q., Siew Ch.Y. Dynamical Cognitive Network – an Extension of Fuzzy Cognitive Map. IEEE Trans. on Fuzzy Systems. 2001; 9; 5: 760–770.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Кузенцов О.П. Когнитивное моделирование слабо структурированных ситуаций [Электрон. ресурс]. Режим доступа: http://posp.raai.org/data/posp2005/Kuznetsov/kuznetsov.html (Дата обращения: 20.10.2021).</mixed-citation><mixed-citation xml:lang="en">Kuzentsov O.P. Kognitivnoye modelirovaniye slabo strukturirovannykh situatsiy = Cognitive modeling of weakly structured situations [Internet]. Available from: http://posp.raai.org/data/posp2005/Kuznetsov/kuznetsov.html</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Eden C. Cognitive mapping // European Journal of Operational Research. 1988. № 36. С. 1–13.</mixed-citation><mixed-citation xml:lang="en">(cited 20.10.2021). (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Абрамова Н.А., Коврига С.В. Некоторые критерии достоверности моделей на основе когнитивных карт // Проблемы управления. 2008. № 6. С. 23–33.</mixed-citation><mixed-citation xml:lang="en">Eden C. Cognitive mapping. European Journal of Operational Research. 1988. 36: 1–13.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Абрамова Н.А., Коврига С.В. О рисках, связанных с ошибками экспертов и аналитиков // Проблемы управления. 2006. № 6. С. 60–67.</mixed-citation><mixed-citation xml:lang="en">Abramova N.A., Kovriga S.V. Some criteria for the reliability of models based on cognitive maps. Problemy upravleniya = Control sciences. 2008; 6: 23–33. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Kosko B. Fuzzy Cognitive Maps // International Journal of Man-Machine Studies. 1986. Т. 24. С. 65–75.</mixed-citation><mixed-citation xml:lang="en">Abramova N.A., Kovriga S.V. On the risks associated with the mistakes of experts and analysts. Problemy upravleniya = Control sciences. 2006; 6: 60–67. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Силов В.Б. Принятие стратегических решений в нечеткой обстановке. М.: ИНПРО– РЕС, 1995.</mixed-citation><mixed-citation xml:lang="en">Kosko B. Fuzzy Cognitive Maps. International Journal of Man-Machine Studies. 1986; 24: 65–75.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Кизим Н.А., Хаустова В.Е. Особенности проверки моделей на основе когнитивных карт на устойчивость и достоверность. В кн. Современные подходы к моделированию сложных социально-экономических систем. Харьков: ФЛП Александрова К. М.; ИД «ИНЖЭК», 2011. 280 с.</mixed-citation><mixed-citation xml:lang="en">Silov V.B. Prinyatiye strategicheskikh resheniy v nechetkoy obstanovke = Making strategic decisions in a fuzzy environment. Moscow: INPRO –RES; 1995. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Горелова Г.В., Захарова Е.Н., Гинис Л.А. Когнитивный анализ и моделирование устойчивого развития социально-экономических систем. Ростов-на-Дону: Ростовский государственный университет, 2005. 288 с.</mixed-citation><mixed-citation xml:lang="en">Kizim N.A., Khaustova V.Ye. Osobennosti proverki modeley na osnove kognitivnykh kart na ustoychivostʹ i dostovernostʹ. V kn. Sovremennyye podkhody k modelirovaniyu slozhnykh sotsialʹnoekonomicheskikh system = Features of checking models based on cognitive maps for stability and reliability. In book. Modern approaches to modeling complex socio-economic systems. Kharkiv: FLP Aleksandrova K. M.; Publishing House «INZHEK»; 2011. 280 p. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Корнеев В.В., Ганеев А.Ф., Васютин С.В., Райх В.В. Базы данных. Интеллектуальная обработка информации. М.: Издательство политики, 2001. 496 с.</mixed-citation><mixed-citation xml:lang="en">Gorelova G.V., Zakharova Ye.N., Ginis L.A. Kognitivnyy analiz i modelirovaniye ustoychivogo razvitiya sotsialʹno-ekonomicheskikh sistem = Cognitive analysis and modeling of sustainable development of socio-economic systems. Rostovon-Don: Rostov State University; 2005. 288 p. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Борисов В.В., Бычков И.А., Дементьев А.В., Соловьев А.П., Федулов А.С. Компьютерная поддержка сложных организационно-технических систем. М.: Горячая линия – Телеком, 2002. 154 с.</mixed-citation><mixed-citation xml:lang="en">Korneyev V.V., Ganeyev A.F., Vasyutin S.V., Raykh V.V. Bazy dannykh. Intellektualʹnaya obrabotka informatsii = Databases. Intelligent information processing. Moscow: I Politics Publishing House; 2001. 496 p. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Поспелов Д.А. Десять «горячих точек» в исследованиях по искусственному интеллекту // Интеллектуальные системы (МГУ). 1996. Т. 1. № 1(4). C. 47–56.</mixed-citation><mixed-citation xml:lang="en">Borisov V.V., Bychkov I.A., DementʹyevA.V., Solovʹyev A.P., Fedulov A.S. Kompʹyuternaya podderzhka slozhnykh organizatsionnotekhnicheskikh system = Computer support for complex organizational and technical systems. Moscow: Hotline – Telecom; 2002. 154 p. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Леденёва Т.М., Моисеев С.А. Формализация свойств интерпретируемых лингвистических шкал и термов нечетких моделей // Прикладная информатика. 2012. № 4(40). С. 126–132.</mixed-citation><mixed-citation xml:lang="en">Pospelov D.A. Ten «hot spots» in artificial intelligence research. Intellektualʹnyye sistemy (MGU) = Intelligent Systems (MSU). 1996; 1; 1(4): 47–56. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Vallido A., Martin-Guerrero J.D., Lisboa P.J.G. Making machine learning models interpretable // Proc. of European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (25-27 April 2012, Bruges) Belgium: Bruges. 2012. С. 163–172.</mixed-citation><mixed-citation xml:lang="en">Ledenëva T.M., Moiseyev S.A. Formalization of properties of interpreted linguistic scales and terms of fuzzy models. Prikladnaya informatika = Applied Informatics. 2012; 4(40): 126–132. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Yoon B.S., Jetter A.J. Comparative analysis for Fuzzy Cognitive Mapping // Proc. of 2016 Portland Intern. Conf. on Management of Engineering and Technology (PICMET). 2016. С. 1897–190.</mixed-citation><mixed-citation xml:lang="en">Vallido A., Martin-Guerrero J.D., Lisboa P.J.G. Making machine learning models interpretable. Proc. of European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (25-27 April 2012, Bruges) Belgium: Bruges. 2012: 163–172.</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Özesmi U., Özesmi S. L. Ecological Models Based on People’s Knowledge: a Multi-Step Fuzzy Cognitive Mapping Approach // Ecological Modelling. 2004. № 176. С. 43–64.</mixed-citation><mixed-citation xml:lang="en">Yoon B.S., Jetter A.J. Comparative analysis for Fuzzy Cognitive Mapping. Proc. of 2016 Portland Intern. Conf. on Management of Engineering and Technology (PICMET). 2016: 1897–190.</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Kosko B. Fuzzy Engineering. New Jersey: Prentice-Hall. 1997.</mixed-citation><mixed-citation xml:lang="en">Özesmi U., Özesmi S. L. Ecological Models Based on People’s Knowledge: a Multi-Step Fuzzy Cognitive Mapping Approach. Ecological Modelling. 2004; 176: 43–64.</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Aguilar J. Adaptive random fuzzy cognitive maps // Ibero-American Conference on Artificial Intelligence. Springer, Berlin, Heidelberg, 2002. С. 402–410.</mixed-citation><mixed-citation xml:lang="en">Kosko B. Fuzzy Engineering. New Jersey: Prentice-Hall. 1997.</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Kosko B. Neural networks and fuzzy systems: A dynamical systems approach to machine intelligence. 1992. 290 p.</mixed-citation><mixed-citation xml:lang="en">Aguilar J. Adaptive random fuzzy cognitive maps. Ibero-American Conference on Artificial Intelligence. Springer, Berlin, Heidelberg, 2002: 402-410.</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Koulouriotis D.E., Diakoulakis I.E., Emiris D.M. Learning fuzzy cognitive maps using evolution strategies: a novel schema for modeling and simulating high-level behavior // Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No. 01TH8546). 2001. Т. 1. С. 364-371.</mixed-citation><mixed-citation xml:lang="en">Kosko B. Neural networks and fuzzy systems: A dynamical systems approach to machine intelligence. 1992. 290 p.</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Аверкин А.Н., Ярушев С.А., Павлов В.Ю. Когнитивные гибридные системы поддержки принятия решений и прогнозирования // Программные продукты и системы. 2017. Т. 30. № 4. С. 632– 642. DOI: 10.15827/0236-235X.030.4.632-642.</mixed-citation><mixed-citation xml:lang="en">Koulouriotis D.E., Diakoulakis I.E., Emiris D.M. Learning fuzzy cognitive maps using evolution strategies: a novel schema for modeling and simulating high-level behavior. Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No. 01TH8546). 2001; 1: 364-371.</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Ефремова Н.А., Аверкин А.Н., Ярушев С.А. Гибридные нечеткие когнитивные карты в задачах принятия решений и прогнозирования // Программные продукты, системы и алгоритмы. 2017. № 4. С. 1–9.</mixed-citation><mixed-citation xml:lang="en">Averkin A.N., Yarushev S.A., Pavlov V.Yu. Cognitive hybrid systems for decision support and forecasting. Programmnyye produkty i sistemy = Software Products and Systems. 2017; 30; 4: 632– 642. DOI: 10.15827/0236-235X.030.4.632-642. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">Кулинич А. Компьютерные системы моделирования когнитивных карт: подходы и методы // Проблемы управления. 2010. № 3. С. 2–16.</mixed-citation><mixed-citation xml:lang="en">Yefremova, N.A., Averkin, A. N., Yarushev, S.A. Hybrid Fuzzy Cognitive Maps in Decision-Making and Forecasting. Programmnyye produkty, sistemy i algoritmy = Software Products, Systems and Algorithms. 2017; 4: 1-9. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit33"><label>33</label><citation-alternatives><mixed-citation xml:lang="ru">Mikryukov A., Mazurov M. The Task of Improving the University Ranking Based on the Statistical Analysis Methods. In: Hu Z., Petoukhov S., He M. (eds) Advances in Artificial Systems for Medicine and Education IV. AIMEE 2020 // Advances in Intelligent Systems and Computing. Springer, Cham. 2021. Т. 1315. DOI: 10.1007/978-3-030-67133-4_6.</mixed-citation><mixed-citation xml:lang="en">Kulinich A. Computer systems for modeling cognitive maps: approaches and methods. Problemy upravleniya = Control Sciences. 2010; 3: 2–16. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit34"><label>34</label><citation-alternatives><mixed-citation xml:lang="ru">Коврига С.В., Телицына Т.А. О методе верификации когнитивных карт, основанном на частных критериях достоверности // XII Всероссийское совещание по проблемам управления ВСПУ-2014 (Москва, 16-19 июня). 2014. С. 4132–4143.</mixed-citation><mixed-citation xml:lang="en">Mikryukov A., Mazurov M. The Task of Improving the University Ranking Based on the Statistical Analysis Methods. In: Hu Z., Petoukhov S., He M. (eds) Advances in Artificial Systems for Medicine and Education IV. AIMEE 2020. Advances in Intelligent Systems and Computing. Springer, Cham. 2021: 1315. DOI: 10.1007/978-3-030-67133-4_6.</mixed-citation></citation-alternatives></ref><ref id="cit35"><label>35</label><citation-alternatives><mixed-citation xml:lang="ru">Гамазов И. Н., Терехов В. И. Анализ задач, возникающих при создании нечетких когнитивных карт [Электрон. ресурс]. Режим доступа: https://cyberleninka.ru/article/n/analizzadach-voznikayuschih-pri-sozdanii-nechetkihkognitivnyh-kart. (Дата обращения: 20.02.2022).</mixed-citation><mixed-citation xml:lang="en">Kovriga S.V., Telitsyna T.A. On the method of verification of cognitive maps based on particular reliability criteria. XII Vserossiyskoye soveshchaniye po problemam upravleniya VSPU-2014 = XII All-Russian Conference on Management Problems VSPU-2014 (Moscow, June 16-19). 2014: 4132– 4143. (In Russ.)</mixed-citation></citation-alternatives></ref><ref id="cit36"><label>36</label><citation-alternatives><mixed-citation xml:lang="ru">Gamazov I. N., Terekhov V. I. Analiz zadach, voznikayushchikh pri sozdanii nechetkikh kognitivnykh kart = Analysis of tasks arising when creating fuzzy cognitive maps [Internet]. Available from: https://cyberleninka.ru/article/n/analizzadach-voznikayuschih-pri-sozdanii-nechetkihkognitivnyh-kart. (cited 20.02.2022). (In Russ.)</mixed-citation><mixed-citation xml:lang="en">Gamazov I. N., Terekhov V. I. Analiz zadach, voznikayushchikh pri sozdanii nechetkikh kognitivnykh kart = Analysis of tasks arising when creating fuzzy cognitive maps [Internet]. Available from: https://cyberleninka.ru/article/n/analizzadach-voznikayuschih-pri-sozdanii-nechetkihkognitivnyh-kart. (cited 20.02.2022). (In Russ.)</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
