Generalizations of fuzzy information measures [electronic resource] /
Ohlan, Anshu.author.
Ohlan, Ramphul.author.
This book develops applications of novel generalizations of fuzzy information measures in the field of pattern recognition, medical diagnosis, multi-criteria and multi-attribute decision making and suitability in linguistic variables. The focus of this presentation lies on introducing consistently strong and efficient generalizations of information and information-theoretic divergence measures in fuzzy and intuitionistic fuzzy environment covering different practical examples. The target audience comprises primarily researchers and practitioners in the involved fields but the book may also be beneficial for graduate students.
Includes bibliographical references at the end of each chapters and index.
Fundamentals of Fuzzy Information Measures -- Parametric Generalized R‒Norm Fuzzy Information and Divergence Measures -- Parametric Generalized R‒Norm Fuzzy Information and Divergence Measures -- Parametric Generalized Exponential Fuzzy Divergence Measure and Strategic Decision Making -- Sequence and Application of Inequalities Among Fuzzy Mean Difference Divergence Measures in Pattern Recognition -- Applications of Generalized Fuzzy Divergence Measure in Multi-criteria Decision Making and Pattern Recognition -- Generalized Hellinger’s Fuzzy Divergence Measure and Its Applications -- Intuitionistic Fuzzy Exponential Divergence and Multi-Attribute Decision Making.
This book develops applications of novel generalizations of fuzzy information measures in the field of pattern recognition, medical diagnosis, multi-criteria and multi-attribute decision making and suitability in linguistic variables. The focus of this presentation lies on introducing consistently strong and efficient generalizations of information and information-theoretic divergence measures in fuzzy and intuitionistic fuzzy environment covering different practical examples. The target audience comprises primarily researchers and practitioners in the involved fields but the book may also be beneficial for graduate students.
Pattern recognition.
Computer mathematics.
Computational complexity.
Biometrics (Biology).
Applied linguistics.
Pattern Recognition.
Computational Science and Engineering.
Complexity.
Biometrics.
Applied Linguistics.