Computing with WordsFuzzy logic refers to a computer's ability to make decisions involving "grey" or "fuzzy" areas. As linguistics contains numerous "grey" areas, computing with words through the use of fuzzy logic is an extremely hot topic in database and Internet research. This book explores the state of the art in linguistic computation, discussing how current research findings are extending the application of fuzzy logic beyond control engineering and intelligent systems into the use of language on a computer. Fuzzy logic pioneer, Dr. Lofti Zadeh, provides the introduction for this thought-provoking work. |
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Page 92
Fuzzy sets and logics possess far greater capability to capture irreducible measurement uncertainties than their ... The capability of fuzzy sets to capture gradual transitions from one set to another considerably enhances their ...
Fuzzy sets and logics possess far greater capability to capture irreducible measurement uncertainties than their ... The capability of fuzzy sets to capture gradual transitions from one set to another considerably enhances their ...
Page 274
F. Herrera , E. Herrera - Viedma , and J. L. Verdegay , Direct approach processes in group decision making using linguistic OWA operators , Fuzzy Sets Syst . , 79 : 175–190 , 1996 . 29. F. Herrera , E. Herrera - Viedma , and J. L. ...
F. Herrera , E. Herrera - Viedma , and J. L. Verdegay , Direct approach processes in group decision making using linguistic OWA operators , Fuzzy Sets Syst . , 79 : 175–190 , 1996 . 29. F. Herrera , E. Herrera - Viedma , and J. L. ...
Page 303
However , descriptive and veristic words are essential for the fundamental derivation of fuzzy set and logic formulas . Descriptive linguistic terms help us assign an element to a fuzzy set with a membership value , whereas veristic ...
However , descriptive and veristic words are essential for the fundamental derivation of fuzzy set and logic formulas . Descriptive linguistic terms help us assign an element to a fuzzy set with a membership value , whereas veristic ...
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Contents
FROM COMPUTING WITH NUMBERS TO COMPUTING WITH | 32 |
THE PROBLEMS | 69 |
GRANULAR RELATIONAL COMPUTING WITH SEMIOTIC | 85 |
Copyright | |
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Common terms and phrases
according adverbs agents algorithms allow analysis applications approach basic called chaotic cognitive communication complex computing with words concept considered constraints context corresponding decision defined Definition described domain dynamic elements entities environment equality example expert expressed extraction Figure formal function fuzzy logic fuzzy relations fuzzy set given granularity granulation human identified important inference intelligent internal interpretation knowledge learning linguistic mathematical meaning methods modified natural language objects observed operator particular perceptions performance phrase points possible precision presented principle probability problem procedures properties propositions query Question reasoning reference representation represented respectively rules semantic semiotic sense sentence shown shows signal situations space specific speech structures symbols Syst t-norms Table texts theory tion truth understanding University values variables verb weighted Zadeh
Bibliographic information
| Title | Computing with Words Volume 3 of Wiley Series on Intelligent Systems |
| Editor | Paul P. Wang |
| Edition | illustrated |
| Publisher | Wiley, 2001 |
| Original from | the University of Michigan |
| Digitized | 20 Nov 2007 |
| ISBN | 0471353744, 9780471353744 |
| Length | 466 pages |
| Export Citation | BiBTeX EndNote RefMan |