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

Analysis and comparison of metaheuri...

Cuevas, Erik.

FindBook

Google Book

Amazon

博客來

Analysis and comparison of metaheuristics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Analysis and comparison of metaheuristics/ by Erik Cuevas, Omar Avalos, Jorge Gálvez.
作者:	Cuevas, Erik.
其他作者:	Avalos, Omar.
出版者:	Cham :Springer International Publishing : : 2023.,
面頁冊數:	xiv, 220 p. :ill., digital ;24 cm.
內容註:	Fundamentals of Metaheuristic Computation -- A Comparative Approach for Two-Dimensional Digital IIR Filter Design Applying Different Evolutionary Computational Techniques -- Comparison of Metaheuristics for Chaotic Systems Estimation -- Comparison Study of Novel Evolutionary Algorithms for Elliptical Shapes in Images -- IIR System Identification using Several Optimization Techniques: A Review Analysis -- Fractional-order Estimation using Locust Search Algorithm -- Comparison of Optimization Techniques for Solar Cells Parameter Identification -- Comparison of Metaheuristics Techniques and Agent-Based Approaches.
Contained By:	Springer Nature eBook
標題:	Metaheuristics. -
電子資源:	https://doi.org/10.1007/978-3-031-20105-9
ISBN:	9783031201059

Analysis and comparison of metaheuristics
Cuevas, Erik.

Analysis and comparison of metaheuristics[electronic resource] /by Erik Cuevas, Omar Avalos, Jorge Gálvez. - Cham :Springer International Publishing :2023. - xiv, 220 p. :ill., digital ;24 cm. - Studies in computational intelligence,v. 10631860-9503 ;. - Studies in computational intelligence ;v. 1063..

Fundamentals of Metaheuristic Computation -- A Comparative Approach for Two-Dimensional Digital IIR Filter Design Applying Different Evolutionary Computational Techniques -- Comparison of Metaheuristics for Chaotic Systems Estimation -- Comparison Study of Novel Evolutionary Algorithms for Elliptical Shapes in Images -- IIR System Identification using Several Optimization Techniques: A Review Analysis -- Fractional-order Estimation using Locust Search Algorithm -- Comparison of Optimization Techniques for Solar Cells Parameter Identification -- Comparison of Metaheuristics Techniques and Agent-Based Approaches.

This book presents a comparative perspective of current metaheuristic developments, which have proved to be effective in their application to several complex problems. The study of biological and social entities such as animals, humans, or insects that manifest a cooperative behavior has produced several computational models in metaheuristic methods. Although these schemes emulate very different processes or systems, the rules used to model individual behavior are very similar. Under such conditions, it is not clear to identify which are the advantages or disadvantages of each metaheuristic technique. The book is compiled from a teaching perspective. For this reason, the book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. It is appropriate for courses such as Artificial Intelligence, Electrical Engineering, Evolutionary Computation. The book is also useful for researchers from the evolutionary and engineering communities. Likewise, engineer practitioners, who are not familiar with metaheuristic computation concepts, will appreciate that the techniques discussed are beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise in engineering areas.

ISBN: 9783031201059

Standard No.: 10.1007/978-3-031-20105-9doiSubjects--Topical Terms:

2206834
Metaheuristics.

LC Class. No.: QA76.9.A43

Dewey Class. No.: 005.1

Analysis and comparison of metaheuristics
LDR:02994nmm a2200337 a 4500 001 2314898
003 DE-He213
005 20221102044057.0
006 m d
007 cr nn 008maaau
008 230902s2023 sz s 0 eng d
020 $a 9783031201059 $q (electronic bk.)
020 $a 9783031201042 $q (paper)
024 7 $a 10.1007/978-3-031-20105-9 $2 doi
035 $a 978-3-031-20105-9
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.A43
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 005.1 $2 23
090 $a QA76.9.A43 $b C965 2023
100 1 $a Cuevas, Erik. $3 2180030
245 1 0 $a Analysis and comparison of metaheuristics $h [electronic resource] / $c by Erik Cuevas, Omar Avalos, Jorge Gálvez.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2023.
300 $a xiv, 220 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-9503 ; $v v. 1063
505 0 $a Fundamentals of Metaheuristic Computation -- A Comparative Approach for Two-Dimensional Digital IIR Filter Design Applying Different Evolutionary Computational Techniques -- Comparison of Metaheuristics for Chaotic Systems Estimation -- Comparison Study of Novel Evolutionary Algorithms for Elliptical Shapes in Images -- IIR System Identification using Several Optimization Techniques: A Review Analysis -- Fractional-order Estimation using Locust Search Algorithm -- Comparison of Optimization Techniques for Solar Cells Parameter Identification -- Comparison of Metaheuristics Techniques and Agent-Based Approaches.
520 $a This book presents a comparative perspective of current metaheuristic developments, which have proved to be effective in their application to several complex problems. The study of biological and social entities such as animals, humans, or insects that manifest a cooperative behavior has produced several computational models in metaheuristic methods. Although these schemes emulate very different processes or systems, the rules used to model individual behavior are very similar. Under such conditions, it is not clear to identify which are the advantages or disadvantages of each metaheuristic technique. The book is compiled from a teaching perspective. For this reason, the book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. It is appropriate for courses such as Artificial Intelligence, Electrical Engineering, Evolutionary Computation. The book is also useful for researchers from the evolutionary and engineering communities. Likewise, engineer practitioners, who are not familiar with metaheuristic computation concepts, will appreciate that the techniques discussed are beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise in engineering areas.
650 0 $a Metaheuristics. $3 2206834
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Avalos, Omar. $3 3530239
700 1 $a Gálvez, Jorge. $3 3626773
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Studies in computational intelligence ; $v v. 1063. $3 3626774
856 4 0 $u https://doi.org/10.1007/978-3-031-20105-9
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)