國立虎尾科技大學 |

Uncertainty Data in Interval-Valued Fuzzy Set Theory = Properties, Algorithms and Applications /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Uncertainty Data in Interval-Valued Fuzzy Set Theory/ by Barbara Pękala.
Reminder of title:	Properties, Algorithms and Applications /
Author:	Pękala, Barbara.
Description:	XIV, 181 p. 12 illus.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-3-319-93910-0
ISBN:	9783319939100

Uncertainty Data in Interval-Valued Fuzzy Set Theory = Properties, Algorithms and Applications /
Pękala, Barbara.

Uncertainty Data in Interval-Valued Fuzzy Set TheoryProperties, Algorithms and Applications /[electronic resource] :by Barbara Pękala. - 1st ed. 2019. - XIV, 181 p. 12 illus.online resource. - Studies in Fuzziness and Soft Computing,3671434-9922 ;. - Studies in Fuzziness and Soft Computing,319.

Introduction to Fuzzy Sets -- Interval-Valued Fuzzy Relations -- Applications -- Summary and Open Problem.

This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov’s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data. .

ISBN: 9783319939100

Standard No.: 10.1007/978-3-319-93910-0doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Uncertainty Data in Interval-Valued Fuzzy Set Theory = Properties, Algorithms and Applications /
LDR:02621nam a22004095i 4500 001 1009836
003 DE-He213
005 20200706033305.0
007 cr nn 008mamaa
008 210106s2019 gw | s |||| 0|eng d
020 $a 9783319939100 $9 978-3-319-93910-0
024 7 $a 10.1007/978-3-319-93910-0 $2 doi
035 $a 978-3-319-93910-0
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
100 1 $a Pękala, Barbara. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1303851
245 1 0 $a Uncertainty Data in Interval-Valued Fuzzy Set Theory $h [electronic resource] : $b Properties, Algorithms and Applications / $c by Barbara Pękala.
250 $a 1st ed. 2019.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a XIV, 181 p. 12 illus. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Studies in Fuzziness and Soft Computing, $x 1434-9922 ; $v 367
505 0 $a Introduction to Fuzzy Sets -- Interval-Valued Fuzzy Relations -- Applications -- Summary and Open Problem.
520 $a This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov’s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data. .
650 0 $a Computational intelligence. $3 568984
650 0 $a Operations research. $3 573517
650 0 $a Management science. $3 719678
650 0 $a Artificial intelligence. $3 559380
650 0 $a Decision making. $3 528319
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Operations Research, Management Science. $3 785065
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Operations Research/Decision Theory. $3 669176
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319939094
776 0 8 $i Printed edition: $z 9783319939117
776 0 8 $i Printed edition: $z 9783030067434
830 0 $a Studies in Fuzziness and Soft Computing, $x 1434-9922 ; $v 319 $3 1253810
856 4 0 $u https://doi.org/10.1007/978-3-319-93910-0
912 $a ZDB-2-INR
912 $a ZDB-2-SXIT
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)
950 $a Intelligent Technologies and Robotics (R0) (SpringerNature-43728)