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Topics in rough set theory = current...

Akama, Seiki.

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Topics in rough set theory = current applications to granular computing /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Topics in rough set theory/ by Seiki Akama, Yasuo Kudo, Tetsuya Murai.
Reminder of title:	current applications to granular computing /
Author:	Akama, Seiki.
other author:	Kudo, Yasuo.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xv, 201 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Overview of Rough Set Theory -- Object Reduction in Rough Set Theory.
Contained By:	Springer eBooks
Subject:	Rough sets. -
Online resource:	https://doi.org/10.1007/978-3-030-29566-0
ISBN:	9783030295660

Topics in rough set theory = current applications to granular computing /
Akama, Seiki.

Topics in rough set theorycurrent applications to granular computing /[electronic resource] :by Seiki Akama, Yasuo Kudo, Tetsuya Murai. - Cham :Springer International Publishing :2020. - xv, 201 p. :ill., digital ;24 cm. - Intelligent systems reference library,v.1681868-4394 ;. - Intelligent systems reference library ;v.168..

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.

ISBN: 9783030295660

Standard No.: 10.1007/978-3-030-29566-0doiSubjects--Topical Terms:

577805
Rough sets.

LC Class. No.: QA248

Dewey Class. No.: 551.322

Topics in rough set theory = current applications to granular computing /
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100 1 $a Akama, Seiki. $3 2132615
245 1 0 $a Topics in rough set theory $h [electronic resource] : $b current applications to granular computing / $c by Seiki Akama, Yasuo Kudo, Tetsuya Murai.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xv, 201 p. : $b ill., digital ; $c 24 cm.
490 1 $a Intelligent systems reference library, $x 1868-4394 ; $v v.168
505 0 $a Introduction -- Overview of Rough Set Theory -- Object Reduction in Rough Set Theory.
520 $a 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.
650 0 $a Rough sets. $3 577805
650 0 $a Granular computing. $3 590271
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Kudo, Yasuo. $3 3299788
700 1 $a Murai, Tetsuya. $3 3299787
710 2 $a SpringerLink (Online service) $3 836513
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830 0 $a Intelligent systems reference library ; $v v.168. $3 3443971
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950 $a Intelligent Technologies and Robotics (Springer-42732)