AE4M33RZN, Fuzzy logic: Fuzzy relations

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AE4M33RZN, Fuzzy logic: Fuzzy relations

AE4M33RZN, Fuzzy logic: Fuzzy relations

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<strong>Fuzzy</strong> inclusion (non-generalized)<br />

Definition<br />

The fuzzy inclusion ⊆ is a predicate (assigns a true/false value) which<br />

hold for two fuzzy sets A, B ∈

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Klasické plánování

Prohledávání stavového prostoru I: BFS & DFS

Vytěžování dat – přednáška 9

Vytěžování dat – přednáška 7

Evolutionary Algorithms: Introduction Jiˇr´ı Kubal´ık Department of ...

Deskripcn´ı logika

(CSP – Constraint Satisfaction Problems) Jiˇr´ı

Classical Planning

Vytežování Dat Prednáška 11 – Testování modelu: krížová validace ...

RANSAC [Fischler, Bolles '81]

Neinformované metody prohledáván´ı stavového prostoru Michal ...

Klasické plánování II a rozvrhování

Planning: Part 3 Planning Graphs

Co je rozhodovací strom?

<strong>Fuzzy</strong> inclusion (non-generalized) Definition The fuzzy inclusion ⊆ is a predicate (assigns a true/false value) which hold for two fuzzy sets A, B ∈

Page 1 and 2: AE4M33RZN, Fuzzy logic: Fuzzy relat
Page 3: Fuzzy implication We already know f
Page 13: Generalized fuzzy inclusion: Exampl
Page 19 and 20: Google: “fuzzy” Sources: M. Tay
Page 21 and 22: Fuzzy vs. probability • Vagueness
Page 23 and 24: Crisp relations: Inverse Definition
Page 25 and 26: Fuzzy relations Definition A binary
Page 27 and 28: Projection: Example R y 1 y 2 y 3 y
Page 29 and 30: Cylindrical extension: Drawing ⎧
Page 31 and 32: Example of a fuzzy relation ⎧ ⎪
Page 33 and 34: Properties in a finite domain If th
Page 35 and 36: Theorem 234. Let R, S and T be rela
Page 37 and 38: Proof of 234 (contd.). S =
Page 40: Bibliography Navara, M. and Olšák