Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions: 806 (Studies in Computational Intelligence, 806) - Tapa dura
Sinopsis
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.
"Sinopsis" puede pertenecer a otra edición de este libro.
De la contraportada
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.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Advances in Optimization Algorithms for Multidisciplinary Engineering Applicatio (eng)
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Advances in Optimization Algorithms for Multidisciplinary Engineering Applicatio (eng)
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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions (Hardcover)
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Springer International Publishing AG, Cham, 2025
ISBN 10: 3031784391
ISBN 13: 9783031784392
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Hardcover. Condición: 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. Nº de ref. del artículo: 9783031784392
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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions
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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions
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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions
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Springer, Springer Apr 2025, 2025
ISBN 10: 3031784391
ISBN 13: 9783031784392
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Buch. Condición: 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. 820 pp. Englisch. Nº de ref. del artículo: 9783031784392
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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions (Hardcover)
Publicado por
Springer International Publishing AG, Cham, 2025
ISBN 10: 3031784391
ISBN 13: 9783031784392
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Hardcover. Condición: 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. Nº de ref. del artículo: 9783031784392
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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions
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Springer, Springer Apr 2025, 2025
ISBN 10: 3031784391
ISBN 13: 9783031784392
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Buch. Condición: 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 KG, Sachsenplatz 4-6, 1201 Wien 820 pp. Englisch. Nº de ref. del artículo: 9783031784392
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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Buch. Condición: 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. Nº de ref. del artículo: 9783031784392
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Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions (Studies in Computational Intelligence, 806)
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