國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Nature-inspired computing and optimi...

Nakamatsu, Kazumi.

Nature-inspired computing and optimizationtheory and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Nature-inspired computing and optimizationedited by Srikanta Patnaik, Xin-She Yang, Kazumi Nakamatsu.
其他題名:	theory and applications /
其他作者:	Patnaik, Srikanta.
出版者:	Cham :Springer International Publishing :2017.
面頁冊數:	xxi, 494 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Natural computation.
電子資源:	http://dx.doi.org/10.1007/978-3-319-50920-4
ISBN:	9783319509204$q(electronic bk.)

Nature-inspired computing and optimizationtheory and applications /
Nature-inspired computing and optimizationtheory and applications /[electronic resource] :edited by Srikanta Patnaik, Xin-She Yang, Kazumi Nakamatsu. - Cham :Springer International Publishing :2017. - xxi, 494 p. :ill. (some col.), digital ;24 cm. - Modeling and optimization in science and technologies,v.102196-7326 ;. - Modeling and optimization in science and technologies ;v.2..

From the content: The Nature of Nature: Why Nature Inspired Algorithms Work -- Improved Bat Algorithm in Noise-Free and Noisy Environments -- Multi-objective Ant Colony Optimisation in Wireless Sensor Networks.le.

The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.

ISBN: 9783319509204$q(electronic bk.)

Standard No.: 10.1007/978-3-319-50920-4doiSubjects--Topical Terms:

339160
Natural computation.

LC Class. No.: QA76.9.N37

Dewey Class. No.: 006.38

Nature-inspired computing and optimizationtheory and applications /
LDR:02539nmm a2200325 a 4500 001 509117
003 DE-He213
005 20170911142517.0
006 m d
007 cr nn 008maaau
008 171121s2017 gw s 0 eng d
020 $a 9783319509204$q(electronic bk.)
020 $a 9783319509198$q(paper)
024 7 $a 10.1007/978-3-319-50920-4 $2 doi
035 $a 978-3-319-50920-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.N37
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 006.38 $2 23
090 $a QA76.9.N37 $b N285 2017
245 0 0 $a Nature-inspired computing and optimization $h [electronic resource] : $b theory and applications / $c edited by Srikanta Patnaik, Xin-She Yang, Kazumi Nakamatsu.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a xxi, 494 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Modeling and optimization in science and technologies, $x 2196-7326 ; $v v.10
505 0 $a From the content: The Nature of Nature: Why Nature Inspired Algorithms Work -- Improved Bat Algorithm in Noise-Free and Noisy Environments -- Multi-objective Ant Colony Optimisation in Wireless Sensor Networks.le.
520 $a The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.
650 0 $a Natural computation. $3 339160
650 0 $a Mathematical optimization. $3 183292
650 1 4 $a Engineering. $3 210888
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Optimization. $3 274084
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 252959
650 2 4 $a Simulation and Modeling. $3 273719
650 2 4 $a Engineering Economics, Organization, Logistics, Marketing. $3 274009
700 1 $a Patnaik, Srikanta. $3 278789
700 1 $a Yang, Xin-She. $3 522569
700 1 $a Nakamatsu, Kazumi. $3 348479
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Modeling and optimization in science and technologies ; $v v.2. $3 674885
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-50920-4
950 $a Engineering (Springer-11647)