PPT-Fuzzy Searches

Fuzzy searching allows you to search for words with similar spelling to the entered search word It can be a useful way to ensure that you dont miss search terms that have been misspelled or spelled in a different way than you anticipated. Allow for fractions partial data imprecise data Fuzzify the data you have How red is this 1 RGB value 150255 What Is a Fuzzy Controller What Is a Fuzzy Controller Simply put it is fuzzy code designed to control something usually mechanical They ca Lecture . 2 Fuzzy Set. Basil Hamed. Electrical Engineering . Islamic University of Gaza. Content. Crisp Sets. Fuzzy Sets. Set-Theoretic . Operations. Extension Principle. Fuzzy . Relations. Dr Basil Hamed. Fuzzy Logic. Lotfi. . Zadeh. (professor at UC Berkeley) wrote his original paper on . fuzzy set theory. . In various occasions, this is what he said…. “Fuzzy logic is a means of presenting problems to computers in a way akin to the way humans solve them”. Chapter 12. M. Tim . Jones. See also . http. ://en.wikipedia.org/wiki/Fuzzy_logic. Fuzzy Sets. . Rules of thumb frequently stated in “fuzzy” linguistic terms.. John is . tall. .. If . someone is . Outline. Graph and fuzzy graph. Characteristics of fuzzy relations. Types of fuzzy relations. Graph and fuzzy graph. Graph. Graph and fuzzy graph. Fuzzy graph. ~. V : . is fuzzy node. ~. Graph and fuzzy graph. Lect. 5 . Fuzzy Logic Control. Basil . Hamed. Electrical Engineering . Islamic University of Gaza. Content. Classical Control. Fuzzy Logic Control. The Architecture of Fuzzy Inference . Systems. Fuzzy Control Model. Abby . yinger. Definitions. Set – any well defined collection of objects. An object in a set is called an element or member of that set. .. Crisp Sets – these are sets that only have values of 0 (‘False’) and 1 (‘True’).. by: Ashley Reynolds. Where Fuzzy Logic Falls in the Field of Mathematics . Mathematics. Mathematical Logic and Foundations. Fuzzy Logic. Computer Science. Logic in Artificial Intelligence. Reasoning Under Uncertainty . Outline. The importance of instance selection. Rough set theory. Fuzzy-rough sets. Fuzzy-rough instance selection. Experimentation. Conclusion. Knowledge discovery. The problem of too much data. Requires storage. Martin Köhler. DLR Oberpfaffenhofen. 8th European Conference on . Severe. . Storms – ECSS 2015. 14 – 18 September 2015, Wiener Neustadt, Austria. Adverse. . weather. . is. . responsible. . for. Enhancing flexibility a. nd. . adaptab. i. lity. of . workf. l. ow. management systems by their integration with fuzzy . ontologies. Václav Slavíček. University . of. Hradec Králové. Faculty of Informatics and Management. Lect. 3 Membership Function and Approximate Reasoning. Basil Hamed. Electrical Engineering . Islamic University of Gaza. Content. . Membership Function. . Features . of Membership Function. . Fuzzy Membership . Proposition. 2. Logic variable. 3. Basic connectives for logic variables. 4. (1) Negation. (2) Conjunction. 5. (3) Disjunction. (4) Implication. Basic connectives for logic variables. Logical function. Pure fuzzy system. TSK fuzzy systems. Fuzzy system with fuzzier and . defuzzier. Fuzzy system as open-loop controller. Fuzzy system as . closed-loop . controller. Fuzzy washing machine. They were produced by Matsushita Electric Industrial Company in .