Luciana Takata Gomes, Laécio Carvalho de Barros, Barnabas's Fuzzy Differential Equations in Various Approaches PDF

By Luciana Takata Gomes, Laécio Carvalho de Barros, Barnabas Bede

ISBN-10: 331922574X

ISBN-13: 9783319225746

ISBN-10: 3319225758

ISBN-13: 9783319225753

This publication can be used as reference for graduate scholars attracted to fuzzy differential equations and researchers operating in fuzzy units and structures, dynamical structures, uncertainty research, and functions of doubtful dynamical platforms. starting with a ancient evaluate and advent to basic notions of fuzzy units, together with diverse probabilities of fuzzy differentiation and metric areas, this e-book strikes directly to an summary of fuzzy calculus thorough exposition and comparability of other ways. leading edge theories of fuzzy calculus and fuzzy differential equations utilizing fuzzy bunches of capabilities are brought and explored. Launching with a quick evaluation of crucial theories, this ebook investigates either recognized and novel methods during this box; corresponding to the Hukuhara differentiability and its generalizations in addition to differential inclusions and Zadeh’s extension. via a special research, result of these kind of theories are tested and compared.

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Y/ \ ŒA0 ¤ ¿. y/ \ ŒA0 with ˛. ŒA˛ /. 28) follows from (i) and (ii). 6. 5 and it has a wider application. 6 (Extension Principle [29, 36]). Let U and V be two topological spaces and F W U ! V/ a function. 31) x2U for all y 2 V. 3 Fuzzy Arithmetics for Fuzzy Numbers The ˛-cuts of fuzzy numbers are closed intervals so it is inevitable the influence of the concepts of the interval arithmetic on the arithmetic of fuzzy numbers. The first fuzzy arithmetic approach presented in this study is equivalent to the interval arithmetic with ˛-cuts of fuzzy numbers.

48) for all ˛ 2 Œ0; 1. 5. Let A be the symmetrical triangular fuzzy number with support Œ a; a, a > 0. The fuzzy function F. Œ0; TI R// such that ŒF. /˛ D ff . 49) 52 3 Fuzzy Calculus where f . / W Œ0; T ! 10, one needs to explicit the membership function of A and F: 8 ˆ ˆ < a C 1; if a Ä < 0 A. f / ¤ 0. t/ D t with 2 ŒA˛ , that is, y D t2 =2. RO . F t2 =2/ D supR f D D D supR t2 =2 . f / F. t/ . t/ 8F < a C 1; if a Ä < 0 D C 1; if 0 Ä < a : a 0; otherwise D A . 54) or ŒF. /˛ D ff .

Keresztfalvi, t-norm-based addition of fuzzy intervals. Fuzzy Sets Syst. 51, 155–159 (1992) 14. A. F. E. G. Fatullayev, A new approach to nonhomogeneous fuzzy initial value problem. Comput. Model. Eng. Sci. 85, 367–378 (2012) 15. T. C. Barros, A note on the generalized difference and the generalized differentiability. Fuzzy Sets Syst. (2015). 015 16. H. Huang, C. Wu, Approximation of fuzzy functions by regular fuzzy neural networks. Fuzzy Sets Syst. 177, 60–79 (2011) 17. M. Hukuhara, Intégration des applications measurables dont la valeur est un compact convexe.

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Fuzzy Differential Equations in Various Approaches by Luciana Takata Gomes, Laécio Carvalho de Barros, Barnabas Bede

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