Frontiers of Higher Order Fuzzy Sets

by Alireza Sadeghian, Hooman Tahayori

Overview

Frontiers of Higher Order Fuzzy Sets, provides a unified representation theorem for higher order fuzzy sets. The book elaborates on the concept of gradual elements and their integration with the higher order fuzzy sets. This book also is devoted to the introduction of new frameworks based on general T2FSs, IT2FSs, Gradual elements, Shadowed sets and rough sets. Such new frameworks will provide more capable frameworks for real applications. Applications of higher order fuzzy sets in various fields will be discussed. In particular, the properties and characteristics of the new proposed frameworks would be studied. Such frameworks that are the result of the integration of general T2FSs, IT2FSs, gradual elements, shadowed sets and rough sets will be shown to be suitable to be applied in the fields of bioinformatics, business, management, ambient intelligence, medicine, cloud computing and smart grids.

Product Details

ISBN-13:	9781493944514
Publisher:	Springer New York
Publication date:	09/10/2016
Edition description:	Softcover reprint of the original 1st ed. 2015
Pages:	261
Product dimensions:	6.10(w) x 9.25(h) x 0.02(d)

About the Author

Dr. Alireza Sadeghian, PhD and Dr. Hooman Tahayori, PhD are both professors at Ryerson University

Table of Contents

A New Fuzzy Disjointing Difference Operator to Calculate Union and Intersection of Type-2 Fuzzy Sets.- Robustness of Higher Order Fuzzy Sets.- Fuzzy Sets of Higher Type and Higher Order in Fuzzy Modeling.- Recent Advances in Fuzzy System Modeling.- On the use of participatory genetic fuzzy system approach to develop fuzzy models.- Fuzzy Modelling of Economic Institutional Rules.- Modeling the uncertainty of a set of graphs using higher order fuzzy sets.- Time-Series Forecasting via Complex Fuzzy Logic.- Multi-Subject Type-2 Linguistic Summaries of Relational Databases.- Bio-Inspired Optimization of Interval Type-2 Fuzzy Controller Design.- Image Processing and Pattern Recognition with Interval Type-2 Fuzzy Inference Systems.- Big Data Analytic via Soft Computing Paradigms.