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

Evolutionary algorithms and neural n...

Mirjalili, Seyedali.

FindBook

Google Book

Amazon

博客來

Evolutionary algorithms and neural networks = theory and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Evolutionary algorithms and neural networks/ by Seyedali Mirjalili.
其他題名:	theory and applications /
作者:	Mirjalili, Seyedali.
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	xiv, 156 p. :ill., digital ;24 cm.
內容註:	Part I: Evolutionary algorithms -- Introduction to Evolutionary Single-objective Optimisation -- Particle Swarm Optimisation -- Ant Colony Optimization -- Genetic Algorithm -- Biogeography-Based Optimization -- Part II: Evolutionary Neural Networks -- Evolutionary Feedforward Neural Networks -- Evolutionary Multi-Layer Perceptron -- Evolutionary Radial Basis Function Networks -- Evolutionary Deep Neural Networks.
Contained By:	Springer eBooks
標題:	Neural networks (Computer science) -
電子資源:	http://dx.doi.org/10.1007/978-3-319-93025-1
ISBN:	9783319930251

Evolutionary algorithms and neural networks = theory and applications /
Mirjalili, Seyedali.

Evolutionary algorithms and neural networkstheory and applications /[electronic resource] :by Seyedali Mirjalili. - Cham :Springer International Publishing :2019. - xiv, 156 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.7801860-949X ;. - Studies in computational intelligence ;v.780..

Part I: Evolutionary algorithms -- Introduction to Evolutionary Single-objective Optimisation -- Particle Swarm Optimisation -- Ant Colony Optimization -- Genetic Algorithm -- Biogeography-Based Optimization -- Part II: Evolutionary Neural Networks -- Evolutionary Feedforward Neural Networks -- Evolutionary Multi-Layer Perceptron -- Evolutionary Radial Basis Function Networks -- Evolutionary Deep Neural Networks.

This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.

ISBN: 9783319930251

Standard No.: 10.1007/978-3-319-93025-1doiSubjects--Topical Terms:

532070
Neural networks (Computer science)

LC Class. No.: QA76.87 / .M575 2019

Dewey Class. No.: 006.32

Evolutionary algorithms and neural networks = theory and applications /
LDR:02488nmm a2200325 a 4500 001 2176358
003 DE-He213
005 20180626060844.0
006 m d
007 cr nn 008maaau
008 191121s2019 gw s 0 eng d
020 $a 9783319930251 $q (electronic bk.)
020 $a 9783319930244 $q (paper)
024 7 $a 10.1007/978-3-319-93025-1 $2 doi
035 $a 978-3-319-93025-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.87 $b .M575 2019
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 006.32 $2 23
090 $a QA76.87 $b .M675 2019
100 1 $a Mirjalili, Seyedali. $3 3378331
245 1 0 $a Evolutionary algorithms and neural networks $h [electronic resource] : $b theory and applications / $c by Seyedali Mirjalili.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xiv, 156 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.780
505 0 $a Part I: Evolutionary algorithms -- Introduction to Evolutionary Single-objective Optimisation -- Particle Swarm Optimisation -- Ant Colony Optimization -- Genetic Algorithm -- Biogeography-Based Optimization -- Part II: Evolutionary Neural Networks -- Evolutionary Feedforward Neural Networks -- Evolutionary Multi-Layer Perceptron -- Evolutionary Radial Basis Function Networks -- Evolutionary Deep Neural Networks.
520 $a This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.
650 0 $a Neural networks (Computer science) $3 532070
650 0 $a Evolutionary computation. $3 582189
650 1 4 $a Engineering. $3 586835
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Mathematical Models of Cognitive Processes and Neural Networks. $3 1619875
650 2 4 $a Simulation and Modeling. $3 890873
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Studies in computational intelligence ; $v v.780. $3 3378332
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-93025-1
950 $a Engineering (Springer-11647)