Probabilistic Model of Canonically Conjugated Fuzzy Subsets - Couverture souple

Tsintsadze, Magda

 
9783659623264: Probabilistic Model of Canonically Conjugated Fuzzy Subsets
Couverture souple
ISBN 10 : 3659623261 ISBN 13 : 9783659623264
Editeur : LAP LAMBERT Academic Publishing, 2017

Synopsis

Data in informatics is the set of information units. Each information unit can be presented as four: (object, sign, value, plausibility). Inaccuracy belongs to information content ( component “value”), and uncertainty – to its verity (component “plausibility”). For the given various information there exists the contradiction between inaccuracy of expression content and its uncertainty: with the increase of expression accuracy, its uncertainty rises as well and vice versa, uncertain character of information leads to some inaccuracy of the final conclusions, received from this information. We see that from one side these notions are in contradiction in a certain way, and from another side – complete each other upon the data presentation. Generally, fuzzy subset is constructed on the basis of expert estimation of one of these commutating components. Constructed in this way, Fuzzy subset incompletely characterizes the informational unit. We offer the method of construction of the informational unit membership function taking into account both canonically conjugated components simultaneously and hence describing this unit in most complete and optimal way.

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Présentation de l'éditeur

Data in informatics is the set of information units. Each information unit can be presented as four: (object, sign, value, plausibility). Inaccuracy belongs to information content ( component “value”), and uncertainty – to its verity (component “plausibility”). For the given various information there exists the contradiction between inaccuracy of expression content and its uncertainty: with the increase of expression accuracy, its uncertainty rises as well and vice versa, uncertain character of information leads to some inaccuracy of the final conclusions, received from this information. We see that from one side these notions are in contradiction in a certain way, and from another side – complete each other upon the data presentation. Generally, fuzzy subset is constructed on the basis of expert estimation of one of these commutating components. Constructed in this way, Fuzzy subset incompletely characterizes the informational unit. We offer the method of construction of the informational unit membership function taking into account both canonically conjugated components simultaneously and hence describing this unit in most complete and optimal way.

Biographie de l'auteur

Dr Magda Tsintsadze is an Associate Professor at Iv. Javakhishvili Tbilisi State University. She is currently contributing to the San Diego State University Georgia as a Computer Engineering Professor. She has also served as a visiting scholar at the University of Lodz; SUNY Stony Brook, NY; Ca’Foscari University of Venice, Dortmund University,etc.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2017
Langue
anglais
ISBN 10 
3659623261
ISBN 13 
9783659623264
Reliure
Broché
Nombre de pages
80
Coordonnées du fabricant
non disponible
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