By Da Duan, Paolo F Fantoni, Martine De Cock, Mike Nachtegael, Etienne E Kerre

ISBN-10: 9812566902

ISBN-13: 9789812566904

ISBN-10: 9812774114

ISBN-13: 9789812774118

FLINS, initially an acronym for Fuzzy good judgment and clever applied sciences in Nuclear technology, is now prolonged to utilized synthetic Intelligence for utilized examine. The contributions to the 7th within the sequence of FLINS meetings contained during this quantity hide state of the art examine and improvement in utilized man made intelligence for utilized study as a rule and for power/nuclear engineering particularly.

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The ambiguous word is the source ( query) of the fuzzy set ( field or answer). 1. Introduction We know that a key assumption in computing with words is that the information which is conveyed by a proposition expressed in a natural language or word may be represented as a generalized constraint of the form "X isr R", where X is a constrained variable; R is a constraining relation; and r is an indexing variable whose value defines the way in which R constrains X. Thus, if p is a proposition expressed in a natural language, then "X isr R" representing the meaning of p, equivalently, the information conveyed by p.

Example of application of the coverage-level (a-b) and the core-position (c) modifiers. 3. Generalized Positively Modifier In the literature several different linguistic hedges have been proposed. 5, (7) where A '(x) is the fuzzy set resulting from the application of the linguistic hedge to A(x). In [8], the modifier has been generalized by introducing a parameter kGP > 0 for managing the contrast intensification. We further generalize the modifier by inserting a parameter 9 e [0,1] to control the membership value to which the MF changes concavity: A'(x) = ••A'-ix) A{x)f ifA(x)<0 if A(x) > 6.

In order to make this tool more friendly to users, we plan to improve it by embedding the system into another language with graphic interface capabilities. We also plan to extend the above tool to carry out the progress of the program, in terms of the involved logic formulae, so the user can obtain at any time the evaluation of the formula transformed by the program instruction. Acknowledgments This Research has been partially supported by grants MTM2005-08982 and TIN2005-09207 from the Government of Spain.

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Applied Artificial Intelligence by Da Duan, Paolo F Fantoni, Martine De Cock, Mike Nachtegael, Etienne E Kerre


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