Skip to main content

Type-2 Fuzzy Granular Models

  • Book
  • © 2017

Overview

  • o date on current research trends on Granular Computing
  • Analyzes the general properties of some core concepts of Granular Computing, such as the information granulation, the principle of justifiable granularity, and higher-type information granule formation
  • All information granules are represented via Fuzzy Sets and all proposed approaches derivate of hybrid intelligent algorithms, such that they automate the modeling from raw data to final fuzzy granular model
  • Several contributions to the area of Granular Computing are presented: a nature inspired granulating algorithm, various techniques for forming higher-type information granules, and an application comparison of various types of information granules
  • Reference for engineers who wish to dwell into applications of more complex algorithms inspired by Granular Computing, for aspiring graduate students who desire to better understand how information granules can be formed, and for scientists who want to keep up t
  • Includes supplementary material: sn.pub/extras

Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)

Part of the book sub series: SpringerBriefs in Computational Intelligence (BRIEFSINTELL)

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (5 chapters)

Keywords

About this book

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.

Authors and Affiliations

  • Faculty of Chemical Sciences and Enginee, Autonomous University of Baja California Faculty of Chemical Sciences and Enginee, Tijuana, Mexico

    Mauricio A. Sanchez, Juan R. Castro

  • Division of Graduate Studies, Tijuana Institute of Technology Division of Graduate Studies, Tijuana, Mexico

    Oscar Castillo

Bibliographic Information

  • Book Title: Type-2 Fuzzy Granular Models

  • Authors: Mauricio A. Sanchez, Oscar Castillo, Juan R. Castro

  • Series Title: SpringerBriefs in Applied Sciences and Technology

  • DOI: https://doi.org/10.1007/978-3-319-41288-7

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: The Author(s) 2017

  • Softcover ISBN: 978-3-319-41287-0Published: 02 September 2016

  • eBook ISBN: 978-3-319-41288-7Published: 26 August 2016

  • Series ISSN: 2191-530X

  • Series E-ISSN: 2191-5318

  • Edition Number: 1

  • Number of Pages: VIII, 93

  • Number of Illustrations: 9 b/w illustrations, 51 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

Publish with us