2021, Vol. 8, No. 1. - go to content...

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DOI: 10.15862/10ECOR121 (https://doi.org/10.15862/10ECOR121)

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Savchenko D.V., Reznikova K.M., Smyshlyaeva A.A. Fuzzy logic and fuzzy information technology. Russian journal of resources, conservation and recycling. 2021; 8(1). Available at: https://resources.today/PDF/10ECOR121.pdf (in Russian). DOI: 10.15862/10ECOR121

Fuzzy logic and fuzzy information technology

Savchenko Denis Valerievich
Far Eastern federal university, Vladivostok, Russia
E-mail: savchenko.dv@students.dvfu.ru

Reznikova Kseniya Mikhailovna
Far Eastern federal university, Vladivostok, Russia
E-mail: a-da_97@mail.ru

Smyshlyaeva Anna Andreevna
Far Eastern federal university, Vladivostok, Russia
E-mail: anyac957@mail.ru

Abstract. With the introduction of the concept of fuzzy logic by Lotfi Zadeh, the world of information technology has changed dramatically, because now there are not two states of the system, as in Boolean logic, but also intermediate states.

In the twentieth century, the world was faced with the fact that existing systems made mistakes due to the accuracy of calculations, which is not applicable to solving real-world problems, but is applicable to solving mathematical problems. It was necessary to create systems that would mimic human thinking to solve complex problems and make decisions in an environment of uncertainty and constantly changing conditions.

The article gives the concept of fuzzy logic, shows the difference between fuzzy logic and Boolean logic. The authors present the history of the concepts of fuzzy logic, fuzzy set, and fuzzy system. Indicate the stages of development of fuzzy logic and the main results of the development of fuzzy logic at these stages. The article presents the architecture of a fuzzy system, explains the main stages of passing data in this system to solve a specific problem. The authors presented a solution to a small decision-making problem, namely, the selection of boxers in the national team, based on fuzzy logic, using the functionality of the MATLAB software product and the Fuzzy Logic Modeler extension.

The article gives the concept of hard and soft computing, their differences from each other. The authors present the main soft computing technologies based on fuzzy logic, and describe their algorithms.

The following are examples of the use of fuzzy logic in the modern world, such as control systems, fuzzy expert systems, automatic systems. Thus, the authors focus on the role of fuzzy logic and fuzzy technologies in everyday life.

Keywords: fuzzy logic; fuzzy set; expert system; automatic system; automated control system; soft computing; fuzzy systems; neural networks; genetic algorithms; probabilistic computing

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