Type-2 Fuzzy Granular Models [electronic resource] /

By:

Sanchez, Mauricio A [author.]

Contributor(s):

Language: ENG Series: SpringerBriefs in Computational IntelligencePublisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017Description: VIII, 93 p. 60 illus., 51 illus. in color. | Binding - Card Paper |Content type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783319412887

Subject(s):

Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:

006.3 23

Online resources:

Click here to access eBook in Springer Nature platform. (Within Campus only.)

In: Springer Nature eBookSummary: 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.

List(s) this item appears in: Springer Nature eBooks

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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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