Type-2 Fuzzy Granular Models
Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing
| Author: | Mauricio A. Sanchez, Oscar Castillo, Juan R. Castro | ISBN: | 9783319412887 |
| Publisher: | Springer International Publishing | Publication: | August 26, 2016 |
| Imprint: | Springer | Language: | English |
| Author: | Mauricio A. Sanchez, Oscar Castillo, Juan R. Castro |
| ISBN: | 9783319412887 |
| Publisher: | Springer International Publishing |
| Publication: | August 26, 2016 |
| Imprint: | Springer |
| Language: | English |
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.
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.
