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Type-2 Fuzzy Granular Models (SpringerBriefs in Computational Intelligence)

By: Juan R. Castro (Author) , Mauricio A. Sanchez (Author) , Oscar Castillo (Author)

Extended Catalogue

Ksh 9,950.00

Format: Paperback or Softback

ISBN-10: 3319412876

ISBN-13: 9783319412870

Collection / Series: SpringerBriefs in Computational Intelligence

Collection Type: Publisher collection

Edition statement: 1st ed. 2017

Publisher: Springer International Publishing AG

Imprint: Springer International Publishing AG

Country of Manufacture: CH

Country of Publication: GB

Publication Date: Sep 2nd, 2016

Publication Status: Active

Product extent: 93 Pages

Product Classification / Subject(s): Fuzzy set theory
Artificial intelligence

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A series of methods for the formation of higher-type information granules represented by Interval Type-2 Fuzzy Sets are also shown, via multiple approaches, such as Coefficient of Variation, principle of justifiable granularity, uncertainty-based information concept, and numerical evidence based.

In this book, a series of granular algorithms are proposed. A nature inspired granular algorithm based on Newtonian gravitational forces is proposed. A series of methods for the formation of higher-type information granules represented by Interval Type-2 Fuzzy Sets are also shown, via multiple approaches, such as Coefficient of Variation, principle of justifiable granularity, uncertainty-based information concept, and numerical evidence based. And a fuzzy granular application comparison is given as to demonstrate the differences in how uncertainty affects the performance of fuzzy information granules.


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