國立虎尾科技大學 |

Interval-Valued Methods in Classifications and Decisions

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Interval-Valued Methods in Classifications and Decisions/ by Urszula Bentkowska.
Author:	Bentkowska, Urszula.
Description:	XV, 163 p. 12 illus., 5 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-3-030-12927-9
ISBN:	9783030129279

Interval-Valued Methods in Classifications and Decisions
Bentkowska, Urszula.

Interval-Valued Methods in Classifications and Decisions[electronic resource] /by Urszula Bentkowska. - 1st ed. 2020. - XV, 163 p. 12 illus., 5 illus. in color.online resource. - Studies in Fuzziness and Soft Computing,3781434-9922 ;. - Studies in Fuzziness and Soft Computing,319.

Fuzzy Sets and their Extensions -- Aggregation in Interval-valued Settings -- Decision Making using Interval-valued Aggregation -- Optimization Problem of k-NN classiﬁer in DNA Microarray Methods -- Interval-valued Methods in Medical Decision Support Systems.

This book describes novel algorithms based on interval-valued fuzzy methods that are expected to improve classification and decision-making processes under incomplete or imprecise information. At first, it introduces interval-valued fuzzy sets. It then discusses new methods for aggregation on interval-valued settings, and the most common properties of interval-valued aggregation operators. It then presents applications such as decision making using interval-valued aggregation, and classification in case of missing values. Interesting applications of the developed algorithms to DNA microarray analysis and in medical decision support systems are shown. The book is intended not only as a timely report for the community working on fuzzy sets and their extensions but also for researchers and practitioners dealing with the problems of uncertain or imperfect information. .

ISBN: 9783030129279

Standard No.: 10.1007/978-3-030-12927-9doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Interval-Valued Methods in Classifications and Decisions
LDR:02597nam a22004095i 4500 001 1026883
003 DE-He213
005 20200704051651.0
007 cr nn 008mamaa
008 210318s2020 gw | s |||| 0|eng d
020 $a 9783030129279 $9 978-3-030-12927-9
024 7 $a 10.1007/978-3-030-12927-9 $2 doi
035 $a 978-3-030-12927-9
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 Bentkowska, Urszula. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1323221
245 1 0 $a Interval-Valued Methods in Classifications and Decisions $h [electronic resource] / $c by Urszula Bentkowska.
250 $a 1st ed. 2020.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a XV, 163 p. 12 illus., 5 illus. in color. $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 378
505 0 $a Fuzzy Sets and their Extensions -- Aggregation in Interval-valued Settings -- Decision Making using Interval-valued Aggregation -- Optimization Problem of k-NN classiﬁer in DNA Microarray Methods -- Interval-valued Methods in Medical Decision Support Systems.
520 $a This book describes novel algorithms based on interval-valued fuzzy methods that are expected to improve classification and decision-making processes under incomplete or imprecise information. At first, it introduces interval-valued fuzzy sets. It then discusses new methods for aggregation on interval-valued settings, and the most common properties of interval-valued aggregation operators. It then presents applications such as decision making using interval-valued aggregation, and classification in case of missing values. Interesting applications of the developed algorithms to DNA microarray analysis and in medical decision support systems are shown. The book is intended not only as a timely report for the community working on fuzzy sets and their extensions but also for researchers and practitioners dealing with the problems of uncertain or imperfect information. .
650 0 $a Computational intelligence. $3 568984
650 0 $a Bioinformatics. $3 583857
650 0 $a Microarrays. $3 891695
650 0 $a Computer simulation. $3 560190
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Computational Biology/Bioinformatics. $3 677363
650 2 4 $a Simulation and Modeling. $3 669249
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030129262
776 0 8 $i Printed edition: $z 9783030129286
776 0 8 $i Printed edition: $z 9783030129293
830 0 $a Studies in Fuzziness and Soft Computing, $x 1434-9922 ; $v 319 $3 1253810
856 4 0 $u https://doi.org/10.1007/978-3-030-12927-9
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)