國立虎尾科技大學 |

New Advancements in Swarm Algorithms: Operators and Applications

Record Type:	Language materials, printed : Monograph/item
Title/Author:	New Advancements in Swarm Algorithms: Operators and Applications/ by Erik Cuevas, Fernando Fausto, Adrián González.
Author:	Cuevas, Erik.
other author:	Fausto, Fernando.
Description:	XV, 296 p.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-3-030-16339-6
ISBN:	9783030163396

New Advancements in Swarm Algorithms: Operators and Applications
Cuevas, Erik.

New Advancements in Swarm Algorithms: Operators and Applications[electronic resource] /by Erik Cuevas, Fernando Fausto, Adrián González. - 1st ed. 2020. - XV, 296 p.online resource. - Intelligent Systems Reference Library,1601868-4394 ;. - Intelligent Systems Reference Library,67.

This book presents advances in alternative swarm development that have proved to be effective in several complex problems. Swarm intelligence (SI) is a problem-solving methodology that results from the cooperation between a set of agents with similar characteristics. The study of biological entities, such as animals and insects, manifesting social behavior has resulted in several computational models of swarm intelligence. While there are numerous books addressing the most widely known swarm methods, namely ant colony algorithms and particle swarm optimization, those discussing new alternative approaches are rare. The focus on developments based on the simple modification of popular swarm methods overlooks the opportunity to discover new techniques and procedures that can be useful in solving problems formulated by the academic and industrial communities. Presenting various novel swarm methods and their practical applications, the book helps researchers, lecturers, engineers and practitioners solve their own optimization problems.

ISBN: 9783030163396

Standard No.: 10.1007/978-3-030-16339-6doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

New Advancements in Swarm Algorithms: Operators and Applications
LDR:02493nam a22003975i 4500 001 1025263
003 DE-He213
005 20200702220854.0
007 cr nn 008mamaa
008 210318s2020 gw | s |||| 0|eng d
020 $a 9783030163396 $9 978-3-030-16339-6
024 7 $a 10.1007/978-3-030-16339-6 $2 doi
035 $a 978-3-030-16339-6
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 Cuevas, Erik. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1102812
245 1 0 $a New Advancements in Swarm Algorithms: Operators and Applications $h [electronic resource] / $c by Erik Cuevas, Fernando Fausto, Adrián González.
250 $a 1st ed. 2020.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a XV, 296 p. $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 Intelligent Systems Reference Library, $x 1868-4394 ; $v 160
520 $a This book presents advances in alternative swarm development that have proved to be effective in several complex problems. Swarm intelligence (SI) is a problem-solving methodology that results from the cooperation between a set of agents with similar characteristics. The study of biological entities, such as animals and insects, manifesting social behavior has resulted in several computational models of swarm intelligence. While there are numerous books addressing the most widely known swarm methods, namely ant colony algorithms and particle swarm optimization, those discussing new alternative approaches are rare. The focus on developments based on the simple modification of popular swarm methods overlooks the opportunity to discover new techniques and procedures that can be useful in solving problems formulated by the academic and industrial communities. Presenting various novel swarm methods and their practical applications, the book helps researchers, lecturers, engineers and practitioners solve their own optimization problems.
650 0 $a Computational intelligence. $3 568984
650 0 $a Artificial intelligence. $3 559380
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Artificial Intelligence. $3 646849
700 1 $a Fausto, Fernando. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1321505
700 1 $a González, Adrián. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1321506
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030163389
776 0 8 $i Printed edition: $z 9783030163402
776 0 8 $i Printed edition: $z 9783030163419
830 0 $a Intelligent Systems Reference Library, $x 1868-4394 ; $v 67 $3 1253823
856 4 0 $u https://doi.org/10.1007/978-3-030-16339-6
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)