This book is dedicated to Prof. Sadaaki Miyamoto and presents cutting-edge papers in some of the areas in which he contributed. Bringing together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as their applications in areas such as decision-making. The book is divided in four parts, the first of which focuses on clustering and classification. The second part puts the spotlight on multisets, bags, fuzzy bags and other fuzzy extensions, while the third deals with rough sets. Rounding out the coverage, the last part explores fuzzy sets and decision-making
The concept of a fuzzy set was introduced by Zadeh in 1965. Fuzzy set is a mathematical model of vag...
This chapter provides a comprehensive, focused introduction to clustering, viewed as a fundamental m...
AbstractFuzzy set theory, soft set theory and rough set theory are mathematical tools for dealing wi...
ABSTRACT: The lesson will begin with the basics of fuzzy set theory. Fuzzy set theory was first intr...
Rough set theory has been used extensively in fields of complexity, cognitive sciences, and artifici...
Rough set theory has been used extensively in fields of complexity, cognitive sciences, and artifici...
Rough set theory is a new method that deals with vagueness and uncertainty emphasized in decision ma...
Fifty years have gone by since the publication of the first paper on clustering based on fuzzy sets ...
„Fuzzy sets and fuzzy logic in multi-criteria decision making. The 50th anniversary of Prof. Lotfi Z...
This book contains the successful invited submissions to a Special Issue of Symmetry in the subject ...
This master thesis deals with cluster analysis, more specifically with clustering methods that use f...
Fuzzy classifiers are important tools in exploratory data analysis, which is a vital set of methods u...
„Fuzzy sets and fuzzy logic in multi-criteria decision making. The 50th anniversary of Prof. Lotfi Z...
This book offers a multifaceted perspective on fuzzy set theory, discussing its developments over th...
Traditional clustering partitions a group of objects into a number of nonoverlapping sets based on a...
The concept of a fuzzy set was introduced by Zadeh in 1965. Fuzzy set is a mathematical model of vag...
This chapter provides a comprehensive, focused introduction to clustering, viewed as a fundamental m...
AbstractFuzzy set theory, soft set theory and rough set theory are mathematical tools for dealing wi...
ABSTRACT: The lesson will begin with the basics of fuzzy set theory. Fuzzy set theory was first intr...
Rough set theory has been used extensively in fields of complexity, cognitive sciences, and artifici...
Rough set theory has been used extensively in fields of complexity, cognitive sciences, and artifici...
Rough set theory is a new method that deals with vagueness and uncertainty emphasized in decision ma...
Fifty years have gone by since the publication of the first paper on clustering based on fuzzy sets ...
„Fuzzy sets and fuzzy logic in multi-criteria decision making. The 50th anniversary of Prof. Lotfi Z...
This book contains the successful invited submissions to a Special Issue of Symmetry in the subject ...
This master thesis deals with cluster analysis, more specifically with clustering methods that use f...
Fuzzy classifiers are important tools in exploratory data analysis, which is a vital set of methods u...
„Fuzzy sets and fuzzy logic in multi-criteria decision making. The 50th anniversary of Prof. Lotfi Z...
This book offers a multifaceted perspective on fuzzy set theory, discussing its developments over th...
Traditional clustering partitions a group of objects into a number of nonoverlapping sets based on a...
The concept of a fuzzy set was introduced by Zadeh in 1965. Fuzzy set is a mathematical model of vag...
This chapter provides a comprehensive, focused introduction to clustering, viewed as a fundamental m...
AbstractFuzzy set theory, soft set theory and rough set theory are mathematical tools for dealing wi...