Ordered Weighted Averaging Aggregation Operator: Fundamentals and Applications
About this ebook
The ordered weighted averaging (OWA) operators give a parameterized class of mean type aggregating operators. These operators can be found in practical mathematics, more notably in fuzzy logic. Ronald R. Yager was the one who first presented them. This class contains a significant number of well-known mean operators, including the maximum, arithmetic average, median, and minimum. Because of their capacity to simulate language conveyed aggregation instructions, they have found widespread application in the field of computational intelligence.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Ordered weighted averaging aggregation operator
Chapter 2: Matrix norm
Chapter 3: Inverse Gaussian distribution
Chapter 4: Expected shortfall
Chapter 5: Uncertainty theory
Chapter 6: Least-squares support vector machine
Chapter 7: Type-1 OWA operators
Chapter 8: Generalized functional linear model
Chapter 9: Birnbaum-Saunders distribution
Chapter 10: Normal basis
(II) Answering the public top questions about ordered weighted averaging aggregation operator.
(III) Real world examples for the usage of ordered weighted averaging aggregation operator in many fields.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of ordered weighted averaging aggregation operator.
