FUZZY RULE BASE DESIGN FOR NUMERICAL DATA ANALYSIS
Ключевые слова:
Fuzzy logic, Rule base design, Numerical data, Membership functions, Fuzzy systems, Decision-making, Uncertainty, Expert systems, Control systems, Data-driven modeling.Аннотация
Fuzzy logic has become increasingly prominent in addressing uncertainties inherent in decision-making processes across various domains. A pivotal component of fuzzy systems is the rule base, which establishes the relationships between inputs and outputs. While traditionally constructed based on expert knowledge or iterative learning from numerical data, there is a growing need to design rule bases solely from numerical data in scenarios lacking expert input. This paper explores methodologies for constructing rule bases from numerical data, considering challenges such as selecting appropriate membership functions and determining rule structures.
Библиографические ссылки
N. R. Yusupbekov, A. R. Marakhimov, H. Z. Igamberdiev, and Sh. X. Umarov. An adaptive fuzzy-logic traffic control system in conditions of saturated transport stream. 2016. The Scientific World Journal Volume 2016 |Article ID 6719459 | https://doi.org/10.1155/2016/6719459.
Y. Ge, “A two-stage fuzzy logic control method of traffic signal based on traffic urgency degree,” Modelling and Simulation in Engineering, vol. 2014, Article ID 694185, 6 pages, 2014.
F. Sattar, F. Karray, M. Kamel, L. Nassar, and K. Golestan, “Recent advances on context-awareness and data/information fusion in ITS,” International Journal of Intelligent Transportation Systems Research, vol. 14, no. 1, pp. 1–19, 2016.
Sidikov I.X., Umurzakova D.M. (2019) Adaptive neuro-fuzzy regulating system of the temperature mode of the drum boiler // International Journal of Advanced Research in Science, Engineering and Technology, 6(1): 7869-7872.
Эргашев О. М., Эргашева Ш. М. Алгоритмы динамической фильтрации с учетом инерции измерительного устройства //Universum: технические науки. – 2020. – №. 2-1 (71).
Mirzapolatovich E. O., Eralievich T. A., Mavlonzhonovich M. M. Analysis of Static Characteristics Optoelectronic Level Converters Liquids and Gases Based on Hollow Light Guides //EUROPEAN JOURNAL OF INNOVATION IN NONFORMAL EDUCATION. – 2022. – Т. 2. – №. 6. – С. 29-31.
Ahmad Kermani, Seyed Mohamad Kargar, Fuzzy modelling of combustion efficiency and control of excess air flow case study: 320-MW steam unit/Isfahan Power Plant/Iran. Clean Energy, Volume 5, Issue 2, June 2021, Pages 229–242, https://doi.org/10.1093/ce/zkab005
Эргашев, О. М. (2018). Обеспечение информационной безопасности радиотехнических систем. Теория и практика современной науки, (6 (36)), 689-691.
Ergashev, O. (2023). АХБОРОТ-КОММУНИКАЦИЯ ТЕХНОЛОГИЯЛАРИНИНГ МАМЛАКАТЛАР РИВОЖЛАНИШИДАГИ АҲАМИЯТИ. Engineering problems and innovations.
Эргашев, О. М. Анализ Процесса Разработка Информационной Системы Предприятия. Innovative developments and research in education, 1(7), 30-35.
Эргашев, О. М. (2023). Интеллектуальный оптоэлектронный прибор для учета и контроля расходом воды в открытых каналах. Al-Farg’oniy avlodlari, 1(4), 60-65.
Mirzapulatovich, E. O. (2023). UNDERWATER REMOTELY CONTROLLED ROBOT FOR CLEANING BOTTOM SPLIT FROM RESERVOIRS AND MAIN CHANNELS. Best Journal of Innovation in Science, Research and Development, 2(11), 717-721.
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