Topics in rough set theory : current applications to granular computing
Akama, Seiki
Topics in rough set theory : current applications to granular computing by Seiki Akama, Yasuo Kudo, Tetsuya Murai - First edition - 1 recurso en línea (XV, 201 páginas) 14 ilustraciones, 1 ilustraciones a color - Intelligent Systems Reference Library 168 1868-4394 Intelligent Technologies and Robotics (Springer-42732) .
Introduction -- Overview of Rough Set Theory -- Object Reduction in Rough Set Theory.
This book discusses current topics in rough set theory. Since Pawlak's rough set theory was first proposed to offer a basis for imprecise and uncertain data and reasoning from data, many workers have investigated its foundations and applications. Examining various topical issues, including object-oriented rough set models, recommendation systems, decision tables, and granular computing, the book is a valuable resource for students and researchers in the field.
9783030295660
10.1007/978-3-030-29566-0 doi
Conjuntos, Teoría de
Soft Computing
Conjuntos, Teoría de
QA248 / 2020 EB
Topics in rough set theory : current applications to granular computing by Seiki Akama, Yasuo Kudo, Tetsuya Murai - First edition - 1 recurso en línea (XV, 201 páginas) 14 ilustraciones, 1 ilustraciones a color - Intelligent Systems Reference Library 168 1868-4394 Intelligent Technologies and Robotics (Springer-42732) .
Introduction -- Overview of Rough Set Theory -- Object Reduction in Rough Set Theory.
This book discusses current topics in rough set theory. Since Pawlak's rough set theory was first proposed to offer a basis for imprecise and uncertain data and reasoning from data, many workers have investigated its foundations and applications. Examining various topical issues, including object-oriented rough set models, recommendation systems, decision tables, and granular computing, the book is a valuable resource for students and researchers in the field.
9783030295660
10.1007/978-3-030-29566-0 doi
Conjuntos, Teoría de
Soft Computing
Conjuntos, Teoría de
QA248 / 2020 EB