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 27
In computing with words , a proposition is viewed as an implicit fuzzy constraint on an implicit variable . ... the initial data set ( IDS ) , which is assumed to consist of a collection of propositions expressed in a natural language .
In computing with words , a proposition is viewed as an implicit fuzzy constraint on an implicit variable . ... the initial data set ( IDS ) , which is assumed to consist of a collection of propositions expressed in a natural language .
Page 28
We are given the following two propositions : > P : The sun is shining outside . Q : A lesson is under way in the classroom . Starting with these two simple propositions , we may construct composite propositions in different ways .
We are given the following two propositions : > P : The sun is shining outside . Q : A lesson is under way in the classroom . Starting with these two simple propositions , we may construct composite propositions in different ways .
Page 53
In computing with words , the starting point is a collection of propositions which play the role of premises . In many cases , canonical forms of these propositions are constraints of the basic , possibilistic type .
In computing with words , the starting point is a collection of propositions which play the role of premises . In many cases , canonical forms of these propositions are constraints of the basic , possibilistic type .
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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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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