Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions

Diego Oliva

ISBN 10: 3031784391 ISBN 13: 9783031784392

Edit� par Springer, 2025

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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.

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Titre : Advances in Optimization Algorithms for ...
�diteur : Springer
Date d'�dition : 2025
Reliure : HRD
Etat : New

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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions

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ISBN 10 : 3031784391 ISBN 13 : 9783031784392

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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions

Diego Oliva (u. a.)

Edit� par Springer, 2025

ISBN 10 : 3031784391 ISBN 13 : 9783031784392

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Buch. Etat : Neu. Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions | Diego Oliva (u. a.) | Buch | xi | Englisch | 2025 | Springer | EAN 9783031784392 | Verantwortliche Person f�r die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N� de r�f. du vendeur 132590572

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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions (Hardcover)

Diego Oliva

Edit� par Springer International Publishing AG, Cham, 2025

ISBN 10 : 3031784391 ISBN 13 : 9783031784392

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Hardcover. Etat : new. Hardcover. 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 sectionsmetaheuristics, 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. 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 sectionsmetaheuristics, machine learning and engineering applications. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N� de r�f. du vendeur 9783031784392

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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions (Hardcover)

Diego Oliva

Edit� par Springer International Publishing AG, Cham, 2025

ISBN 10 : 3031784391 ISBN 13 : 9783031784392

Neuf Couverture rigide

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Hardcover. Etat : new. Hardcover. 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 sectionsmetaheuristics, 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. 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 sectionsmetaheuristics, machine learning and engineering applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de r�f. du vendeur 9783031784392

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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions

Oliva, Diego (Edited by)/ Valdivia, Arturo (Edited by)/ Mousavirad, Seyed Jalaleddin (Edited by)/ Kalita, Kanak (Edited by)

Edit� par Springer, 2025

ISBN 10 : 3031784391 ISBN 13 : 9783031784392

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Hardcover. Etat : Brand New. 817 pages. 9.25x6.10x9.49 inches. In Stock. N� de r�f. du vendeur __3031784391

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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions

Diego Oliva

Edit� par Springer Nature Switzerland, Springer International Publishing Apr 2025, 2025

ISBN 10 : 3031784391 ISBN 13 : 9783031784392

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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 820 pp. Englisch. N� de r�f. du vendeur 9783031784392

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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions

Diego Oliva

Edit� par Springer, Berlin, Springer Nature Switzerland, Springer, 2025

ISBN 10 : 3031784391 ISBN 13 : 9783031784392

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 806 pp. Englisch. N� de r�f. du vendeur 9783031784392

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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions

Diego Oliva

Edit� par Springer Nature Switzerland, Springer International Publishing, 2025

ISBN 10 : 3031784391 ISBN 13 : 9783031784392

Neuf Couverture rigide

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N� de r�f. du vendeur 9783031784392

Contacter le vendeur