國立虎尾科技大學 |

Advances in optimization algorithms for multidisciplinary engineering applications = from classical methods to AI-enhanced solutions /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Advances in optimization algorithms for multidisciplinary engineering applications/ edited by Diego Oliva ... [et al.].
Reminder of title:	from classical methods to AI-enhanced solutions /
other author:	Oliva, Diego.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xi, 806 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
Subject:	Mathematical optimization. -
Online resource:	https://doi.org/10.1007/978-3-031-78440-8
ISBN:	9783031784408

Advances in optimization algorithms for multidisciplinary engineering applications = from classical methods to AI-enhanced solutions /
Advances in optimization algorithms for multidisciplinary engineering applicationsfrom classical methods to AI-enhanced solutions /[electronic resource] :edited by Diego Oliva ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xi, 806 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v. 8061860-9503 ;. - Studies in computational intelligence ;v. 50. .

Metaheuristics theory and applications -- Machine learning -- Engineering applications.

This book is an authoritative compilation of the latest advancements in optimization techniques. This book covers a wide array of methods ranging from classical to metaheuristic to AI-enhanced approaches. The chapters are meticulously selected and organized in three sections-metaheuristics, machine learning and engineering applications. This allows for an in-depth exploration of diverse topics ranging from image processing to feature selection to data clustering, to practical applications like energy optimization, smart grids, healthcare diagnostics, etc. Each chapter delves into the specific algorithms and applications as well as provides ample theoretical insights. Accordingly, this book is ideally suited for undergraduate and postgraduate students in fields such as science, engineering and computational mathematics. It is also an invaluable resource for courses on artificial intelligence, computational intelligence, etc. Researchers and professionals in evolutionary computation, artificial intelligence and engineering will find the material especially useful for advancing their work and exploring new frontiers in optimization.

ISBN: 9783031784408

Standard No.: 10.1007/978-3-031-78440-8doiSubjects--Topical Terms:

527675
Mathematical optimization.

LC Class. No.: QA402.5

Dewey Class. No.: 519.6

Advances in optimization algorithms for multidisciplinary engineering applications = from classical methods to AI-enhanced solutions /
LDR:02399nam a2200337 a 4500 001 1162353
003 DE-He213
005 20250424124704.0
006 m d
007 cr nn 008maaau
008 251029s2025 sz s 0 eng d
020 $a 9783031784408 $q (electronic bk.)
020 $a 9783031784392 $q (paper)
024 7 $a 10.1007/978-3-031-78440-8 $2 doi
035 $a 978-3-031-78440-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA402.5
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 519.6 $2 23
090 $a QA402.5 $b .A244 2025
245 0 0 $a Advances in optimization algorithms for multidisciplinary engineering applications $h [electronic resource] : $b from classical methods to AI-enhanced solutions / $c edited by Diego Oliva ... [et al.].
260 $a Cham : $c 2025. $b Springer Nature Switzerland : $b Imprint: Springer,
300 $a xi, 806 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-9503 ; $v v. 806
505 0 $a Metaheuristics theory and applications -- Machine learning -- Engineering applications.
520 $a This book is an authoritative compilation of the latest advancements in optimization techniques. This book covers a wide array of methods ranging from classical to metaheuristic to AI-enhanced approaches. The chapters are meticulously selected and organized in three sections-metaheuristics, machine learning and engineering applications. This allows for an in-depth exploration of diverse topics ranging from image processing to feature selection to data clustering, to practical applications like energy optimization, smart grids, healthcare diagnostics, etc. Each chapter delves into the specific algorithms and applications as well as provides ample theoretical insights. Accordingly, this book is ideally suited for undergraduate and postgraduate students in fields such as science, engineering and computational mathematics. It is also an invaluable resource for courses on artificial intelligence, computational intelligence, etc. Researchers and professionals in evolutionary computation, artificial intelligence and engineering will find the material especially useful for advancing their work and exploring new frontiers in optimization.
650 0 $a Mathematical optimization. $3 527675
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Artificial Intelligence. $3 646849
700 1 $a Oliva, Diego. $3 1248772
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
830 0 $a Studies in computational intelligence ; $v v. 50. $3 720500 $3 770436
856 4 0 $u https://doi.org/10.1007/978-3-031-78440-8
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)