大葉大學圖書館 |

Natural computing algorithms[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.38
書名/作者:	Natural computing algorithms/ by Anthony Brabazon, Michael O'Neill, Sean McGarraghy.
作者:	Brabazon, Anthony.
其他作者:	O'Neill, Michael.
出版者:	Berlin, Heidelberg : : Springer Berlin Heidelberg :, 2015.
面頁冊數:	xx, 554 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Natural computation.
標題:	Algorithms.
標題:	Computer Science.
標題:	Theory of Computation.
標題:	Computational Intelligence.
標題:	Artificial Intelligence (incl. Robotics)
標題:	Operations Research, Management Science.
標題:	Operation Research/Decision Theory.
標題:	Quantitative Finance.
ISBN:	9783662436318
ISBN:	9783662436301
內容註:	Introduction -- Introduction to Evolutionary Computing -- Genetic Algorithms -- Extending the Genetic Algorithm -- Evolution Strategies and Evolutionary Programming -- Differential Evolution -- Genetic Programming -- Particle Swarm Algorithms -- Ant Algorithms -- Honeybee Algorithms -- Other Social Algorithms -- Bacterial Foraging Algorithms -- Neural Networks for Supervised Learning -- Neural Networks for Unsupervised Learning -- Neuroevolution -- Artificial Immune Systems -- An Introduction to Developmental and Grammatical Computing -- Grammar-Based and Developmental Genetic Programming -- Grammatical Evolution -- TAG3P and Developmental TAG3P -- Genetic Regulatory Networks -- An Introduction to Physics-Inspired Computing -- Physics-Inspired Computing Algorithms -- Quantum-Inspired Evolutionary Algorithms -- Plant-Inspired Algorithms -- Chemistry-Inspired Algorithms -- Conclusions -- References -- Index.
摘要、提要註:	The field of natural computing has been the focus of a substantial research effort in recent decades. One particular strand of this research concerns the development of computational algorithms using metaphorical inspiration from systems and phenomena that occur in the natural world. These naturally inspired computing algorithms have proven to be successful problem-solvers across domains as diverse as management science, bioinformatics, finance, marketing, engineering, architecture and design. This book is a comprehensive introduction to natural computing algorithms, suitable for academic and industrial researchers and for undergraduate and graduate courses on natural computing in computer science, engineering and management science.
電子資源:	http://dx.doi.org/10.1007/978-3-662-43631-8

Natural computing algorithms[electronic resource] /
Brabazon, Anthony.

Natural computing algorithms[electronic resource] /by Anthony Brabazon, Michael O'Neill, Sean McGarraghy. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - xx, 554 p. :ill., digital ;24 cm. - Natural computing series,1619-7127. - Natural computing series..

Introduction -- Introduction to Evolutionary Computing -- Genetic Algorithms -- Extending the Genetic Algorithm -- Evolution Strategies and Evolutionary Programming -- Differential Evolution -- Genetic Programming -- Particle Swarm Algorithms -- Ant Algorithms -- Honeybee Algorithms -- Other Social Algorithms -- Bacterial Foraging Algorithms -- Neural Networks for Supervised Learning -- Neural Networks for Unsupervised Learning -- Neuroevolution -- Artificial Immune Systems -- An Introduction to Developmental and Grammatical Computing -- Grammar-Based and Developmental Genetic Programming -- Grammatical Evolution -- TAG3P and Developmental TAG3P -- Genetic Regulatory Networks -- An Introduction to Physics-Inspired Computing -- Physics-Inspired Computing Algorithms -- Quantum-Inspired Evolutionary Algorithms -- Plant-Inspired Algorithms -- Chemistry-Inspired Algorithms -- Conclusions -- References -- Index.

The field of natural computing has been the focus of a substantial research effort in recent decades. One particular strand of this research concerns the development of computational algorithms using metaphorical inspiration from systems and phenomena that occur in the natural world. These naturally inspired computing algorithms have proven to be successful problem-solvers across domains as diverse as management science, bioinformatics, finance, marketing, engineering, architecture and design. This book is a comprehensive introduction to natural computing algorithms, suitable for academic and industrial researchers and for undergraduate and graduate courses on natural computing in computer science, engineering and management science.

ISBN: 9783662436318

Standard No.: 10.1007/978-3-662-43631-8doiSubjects--Topical Terms:

571196
Natural computation.

LC Class. No.: QA76.9.N37

Dewey Class. No.: 006.38

Natural computing algorithms[electronic resource] /
LDR:02730nam a2200349 a 4500 001 443895
003 DE-He213
005 20160428111304.0
006 m d
007 cr nn 008maaau
008 160715s2015 gw s 0 eng d
020 $a 9783662436318 $q (electronic bk.)
020 $a 9783662436301 $q (paper)
024 7 $a 10.1007/978-3-662-43631-8 $2 doi
035 $a 978-3-662-43631-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.N37
072 7 $a UY $2 bicssc
072 7 $a UYA $2 bicssc
072 7 $a COM014000 $2 bisacsh
072 7 $a COM031000 $2 bisacsh
082 0 4 $a 006.38 $2 23
090 $a QA76.9.N37 $b B795 2015
100 1 $a Brabazon, Anthony. $3 634986
245 1 0 $a Natural computing algorithms $h [electronic resource] / $c by Anthony Brabazon, Michael O'Neill, Sean McGarraghy.
260 $a Berlin, Heidelberg : $b Springer Berlin Heidelberg : $b Imprint: Springer, $c 2015.
300 $a xx, 554 p. : $b ill., digital ; $c 24 cm.
490 1 $a Natural computing series, $x 1619-7127
505 0 $a Introduction -- Introduction to Evolutionary Computing -- Genetic Algorithms -- Extending the Genetic Algorithm -- Evolution Strategies and Evolutionary Programming -- Differential Evolution -- Genetic Programming -- Particle Swarm Algorithms -- Ant Algorithms -- Honeybee Algorithms -- Other Social Algorithms -- Bacterial Foraging Algorithms -- Neural Networks for Supervised Learning -- Neural Networks for Unsupervised Learning -- Neuroevolution -- Artificial Immune Systems -- An Introduction to Developmental and Grammatical Computing -- Grammar-Based and Developmental Genetic Programming -- Grammatical Evolution -- TAG3P and Developmental TAG3P -- Genetic Regulatory Networks -- An Introduction to Physics-Inspired Computing -- Physics-Inspired Computing Algorithms -- Quantum-Inspired Evolutionary Algorithms -- Plant-Inspired Algorithms -- Chemistry-Inspired Algorithms -- Conclusions -- References -- Index.
520 $a The field of natural computing has been the focus of a substantial research effort in recent decades. One particular strand of this research concerns the development of computational algorithms using metaphorical inspiration from systems and phenomena that occur in the natural world. These naturally inspired computing algorithms have proven to be successful problem-solvers across domains as diverse as management science, bioinformatics, finance, marketing, engineering, architecture and design. This book is a comprehensive introduction to natural computing algorithms, suitable for academic and industrial researchers and for undergraduate and graduate courses on natural computing in computer science, engineering and management science.
650 0 $a Natural computation. $3 571196
650 0 $a Algorithms. $3 182797
650 1 4 $a Computer Science. $3 423143
650 2 4 $a Theory of Computation. $3 464054
650 2 4 $a Computational Intelligence. $3 463962
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 463642
650 2 4 $a Operations Research, Management Science. $3 463666
650 2 4 $a Operation Research/Decision Theory. $3 511310
650 2 4 $a Quantitative Finance. $3 464461
700 1 $a O'Neill, Michael. $3 634987
700 1 $a McGarraghy, Sean. $3 634988
710 2 $a SpringerLink (Online service) $3 463450
773 0 $t Springer eBooks
830 0 $a Natural computing series. $3 613971
856 4 0 $u http://dx.doi.org/10.1007/978-3-662-43631-8
950 $a Computer Science (Springer-11645)