By Bing-Yuan Cao, Pei-Zhuang Wang, Zeng-Liang Liu, Yu-Bin Zhong

ISBN-10: 3319308734

ISBN-13: 9783319308739

ISBN-10: 3319308742

ISBN-13: 9783319308746

This lawsuits ebook provides edited result of the 8th overseas convention on Fuzzy info and Engineering (ICFIE'2015) and on Oriental pondering and Fuzzy common sense, in August 17-20, 2015, in Dalian, China. The publication includes sixty five top of the range papers and is split into six major elements: "Fuzzy info Processing", "Fuzzy Engineering", "Internet and massive facts Applications", "Factor area and Factorial Neural Networks", "Information Granulation and Granular Computing" in addition to "Extenics and Innovation Methods".

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**Extra info for International Conference on Oriental Thinking and Fuzzy Logic: Celebration of the 50th Anniversary in the era of Complex Systems and Big Data **

**Example text**

Y. Cao et al. 1007/978-3-319-30874-6_6 43 44 J. Shuang et al. 2 Preliminaries Definition 1 [17] Łukasiewicz t-norm (denoted by) When a, b ???? [0, 1], a L b = (a + b − 1) ∨ 0. And an implication operator adjoin to L : { RL (a, b) = a →L b = L is as follows: 1, a ≤ b; 1 − a + b, a > b. Definition 2 [17] Goguen t-norm (denoted by) When a, b ???? [0, 1], a ???? b = ab. And an implication operator adjoin to ???? : { R???? (a, b) = a →???? b = ???? is as follows: 1, a ≤ b; b , a > b. a Definition 3 (L − λ −???? implication operators) Suppose that ∀ λ ???? [0,1], the fuzzy implication operator R(x, y) = x →λ y of L − λ −???? implication operators is deﬁned as follows, { 1, x ≤ y; x →λ y = y+(1−λ)(1−x) x, y ∈ [0, 1] , x > y.

Definition 5 (Triple I constraint principle for FMT model) [10] Suppose that X, Y are nonempty sets, and F(X), F(Y)are sets of all fuzzy subsets on X, Y. When A(x) ???? F(X), B(y), B∗ (y) ???? F(Y), seek out the smallest A∗ (x) ???? F(X) so that formula (1) have the smallest possibility for all the x ???? Y, y ???? Y. Theorem 1 The fuzzy implication operator R(x, y) = x →λ y of L − λ −???? implication operators is not reducing on the second variable. Fuzzy Reasoning Triple I Constraint Method . . 45 Proof ∀y1 , y2 , suppose 0 ≤ y1 ≤ y2 ≤ 1, we need to discuss in two cases: (1) When x ≤ y1 , that x ≤ y2 , so R(x, y1 ) = x → y1 =1, R(x, y2 ) = x → y2 =1, then R(x, y1 ) = R(x, y2 ); y +(1−λ)(1−x) (2) When x > y1 , R(x, y1 ) = x → y1 = 1 1−λ + x ; λ y +(1−λ)(1−x) Meanwhile, if x > y2 , R(x, y2 ) = x → y2 = 2 1−λ + x , then R(x, y1 ) ≤ R(x, y2 ); λ If x ≤ y2 , R(x, y2 ) = x → y2 =1, obviously R(x, y1 ) ≤ R(x, y2 ).

U∧ (x1i , x2i , … , xmi ; y) = E((f 0 + f 1 x1i + f 2 x2i + ⋯ + f m xmi )−1 (y)) ỹ (7) A Prediction Model for Hot Metal . . 1 Problem Description and Model Establishment The ﬁnal sulfur content measured in the process of hot metal desulfurization has great inﬂuence on the subsequent steelmaking process. However, the ﬁnal sulfur content is closely related to the operation parameters of injection and initial parameters of hot metal. In the desulfurization process, the detection is usually done after completing injection, to test the ﬁnal sulfur content whether it meets the requirement or not.

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