Artificial Intelligence and System Engineering (Paperback)

Radek Silhavy

ISBN 10: 3031967585 / ISBN 13: 9783031967580

Editore: Springer International Publishing AG, Cham, 2025

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Paperback. This book presents cutting-edge research from CoMeSySo 2024, bridging theoretical insights and practical solutions across modern computing. Highlighting data-driven methodologies, innovative modelling, and robust optimization strategies, this book uniquely integrates interdisciplinary approaches to complex computational problems. Through real-world case studies, readers gain actionable insights applicable to diverse fields such as artificial intelligence, cybersecurity, e-learning, and operational logistics.Targeted at academic researchers, industry specialists, and graduate students, the compilation provides valuable frameworks and advanced analytical tools for enhancing performance, efficiency, and decision-making. The presented studies, encompassing adaptive network modelling, deep learning applications, and novel AI-driven frameworks, equip readers to tackle emerging challenges and drive future advancements effectively. The presented studies, encompassing adaptive network modelling, deep learning applications, and novel AI-driven frameworks, equip readers to tackle emerging challenges and drive future advancements effectively. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Codice articolo 9783031967580

Dati bibliografici

• Titolo: Artificial Intelligence and System Engineering (Paperback)
• Editore: Springer International Publishing AG, Cham
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 10: 3031967585
• ISBN 13: 9783031967580
• Rilegatura: Paperback
• Condizione: new

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Riassunto

This book presents cutting-edge research from CoMeSySo 2024, bridging theoretical insights and practical solutions across modern computing. Highlighting data-driven methodologies, innovative modelling, and robust optimization strategies, this book uniquely integrates interdisciplinary approaches to complex computational problems. Through real-world case studies, readers gain actionable insights applicable to diverse fields such as artificial intelligence, cybersecurity, e-learning, and operational logistics.

Targeted at academic researchers, industry specialists, and graduate students, the compilation provides valuable frameworks and advanced analytical tools for enhancing performance, efficiency, and decision-making. The presented studies, encompassing adaptive network modelling, deep learning applications, and novel AI-driven frameworks, equip readers to tackle emerging challenges and drive future advancements effectively.