東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Harmony search algorithm = proceedin...

International Conference on Harmony Search Algorithm (2017 :)

FindBook

Google Book

Amazon

博客來

Harmony search algorithm = proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017) /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Harmony search algorithm/ edited by Javier Del Ser.
其他題名:	proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017) /
其他題名:	ICHSA 2017
其他作者:	Del Ser, Javier.
團體作者:	International Conference on Harmony Search Algorithm
出版者:	Singapore :Springer Singapore : : 2017.,
面頁冊數:	xiv, 366 p. :ill., digital ;24 cm.
內容註:	Sensitivity Analysis on Migration Parameters of Parallel Harmony Search -- Multi-layered Harmony Search Algorithm: Introduction of a Novel and Eﬃcient Structure -- Application of Self-adaptive Method in Multi-objective Harmony Search Algorithm -- A Comparative Study of Exploration Ability of Harmony Search Algorithms -- The Extraordinary Particle Swarm Optimization and its Application in Constrained Engineering Problems -- Metaheuristic based Optimization for Tuned Mass Dampers using Frequency Domain Responses.
Contained By:	Springer eBooks
標題:	Computer algorithms - Congresses. -
電子資源:	http://dx.doi.org/10.1007/978-981-10-3728-3
ISBN:	9789811037283

Harmony search algorithm = proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017) /
Harmony search algorithmproceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017) /[electronic resource] :ICHSA 2017edited by Javier Del Ser. - Singapore :Springer Singapore :2017. - xiv, 366 p. :ill., digital ;24 cm. - Advances in intelligent systems and computing,v.5142194-5357 ;. - Advances in intelligent systems and computing ;v.514..

Sensitivity Analysis on Migration Parameters of Parallel Harmony Search -- Multi-layered Harmony Search Algorithm: Introduction of a Novel and Eﬃcient Structure -- Application of Self-adaptive Method in Multi-objective Harmony Search Algorithm -- A Comparative Study of Exploration Ability of Harmony Search Algorithms -- The Extraordinary Particle Swarm Optimization and its Application in Constrained Engineering Problems -- Metaheuristic based Optimization for Tuned Mass Dampers using Frequency Domain Responses.

This book presents state-of-the-art technical contributions based around one of the most successful evolutionary optimization algorithms published to date: Harmony Search. Contributions span from novel technical derivations of this algorithm to applications in the broad fields of civil engineering, energy, transportation & mobility and health, among many others and focus not only on its cross-domain applicability, but also on its core evolutionary operators, including elements inspired from other meta-heuristics. The global scientific community is witnessing an upsurge in groundbreaking, new advances in all areas of computational intelligence, with a particular flurry of research focusing on evolutionary computation and bio-inspired optimization. Observed processes in nature and sociology have provided the basis for innovative algorithmic developments aimed at leveraging the inherent capability to adapt characterized by various animals, including ants, fireflies, wolves and humans. However, it is the behavioral patterns observed in music composition that motivated the advent of the Harmony Search algorithm, a meta-heuristic optimization algorithm that over the last decade has been shown to dominate other solvers in a plethora of application scenarios. The book consists of a selection of the best contributions presented at ICHSA, a major biannual event where leading global experts on meta-heuristic optimization present their latest findings and discuss the past, present, and future of the exciting field of Harmony Search optimization. It provides a valuable reference resource for researchers working in the field of optimization meta-heuristics, and a solid technical base for frontline investigations around this algorithm.

ISBN: 9789811037283

Standard No.: 10.1007/978-981-10-3728-3doiSubjects--Topical Terms:

576357
Computer algorithms
--Congresses.

LC Class. No.: QA76.9.A43

Dewey Class. No.: 005.1

Harmony search algorithm = proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017) /
LDR:03375nmm a2200337 a 4500 001 2089749
003 DE-He213
005 20170811100533.0
006 m d
007 cr nn 008maaau
008 171013s2017 si s 0 eng d
020 $a 9789811037283 $q (electronic bk.)
020 $a 9789811037276 $q (paper)
024 7 $a 10.1007/978-981-10-3728-3 $2 doi
035 $a 978-981-10-3728-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.A43
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 005.1 $2 23
090 $a QA76.9.A43 $b I61 2017
111 2 $a International Conference on Harmony Search Algorithm $n (3rd : $d 2017 : $c Bilbao, Spain) $3 3220646
245 1 0 $a Harmony search algorithm $h [electronic resource] : $b proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017) / $c edited by Javier Del Ser.
246 3 $a ICHSA 2017
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2017.
300 $a xiv, 366 p. : $b ill., digital ; $c 24 cm.
490 1 $a Advances in intelligent systems and computing, $x 2194-5357 ; $v v.514
505 0 $a Sensitivity Analysis on Migration Parameters of Parallel Harmony Search -- Multi-layered Harmony Search Algorithm: Introduction of a Novel and Eﬃcient Structure -- Application of Self-adaptive Method in Multi-objective Harmony Search Algorithm -- A Comparative Study of Exploration Ability of Harmony Search Algorithms -- The Extraordinary Particle Swarm Optimization and its Application in Constrained Engineering Problems -- Metaheuristic based Optimization for Tuned Mass Dampers using Frequency Domain Responses.
520 $a This book presents state-of-the-art technical contributions based around one of the most successful evolutionary optimization algorithms published to date: Harmony Search. Contributions span from novel technical derivations of this algorithm to applications in the broad fields of civil engineering, energy, transportation & mobility and health, among many others and focus not only on its cross-domain applicability, but also on its core evolutionary operators, including elements inspired from other meta-heuristics. The global scientific community is witnessing an upsurge in groundbreaking, new advances in all areas of computational intelligence, with a particular flurry of research focusing on evolutionary computation and bio-inspired optimization. Observed processes in nature and sociology have provided the basis for innovative algorithmic developments aimed at leveraging the inherent capability to adapt characterized by various animals, including ants, fireflies, wolves and humans. However, it is the behavioral patterns observed in music composition that motivated the advent of the Harmony Search algorithm, a meta-heuristic optimization algorithm that over the last decade has been shown to dominate other solvers in a plethora of application scenarios. The book consists of a selection of the best contributions presented at ICHSA, a major biannual event where leading global experts on meta-heuristic optimization present their latest findings and discuss the past, present, and future of the exciting field of Harmony Search optimization. It provides a valuable reference resource for researchers working in the field of optimization meta-heuristics, and a solid technical base for frontline investigations around this algorithm.
650 0 $a Computer algorithms $x Congresses. $3 576357
650 1 4 $a Engineering. $3 586835
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Computing Methodologies. $3 830243
650 2 4 $a Algorithm Analysis and Problem Complexity. $3 891007
700 1 $a Del Ser, Javier. $3 3220647
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Advances in intelligent systems and computing ; $v v.514. $3 3220648
856 4 0 $u http://dx.doi.org/10.1007/978-981-10-3728-3
950 $a Engineering (Springer-11647)