Artificial Intelligence and System Engineering : Proceedings of 8th Computational Methods in Systems and Software 2024, Volume 2

Radek Silhavy

ISBN 10: 3031967585 / ISBN 13: 9783031967580

Verlag: Springer, Berlin, Springer Nature Switzerland, Springer, 2025

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - 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.

Bestandsnummer des Verkäufers 9783031967580

Bibliografische Details

• Titel: Artificial Intelligence and System Engineering : Proceedings of 8th Computational Methods in Systems and Software 2024, Volume 2
• Verlag: Springer, Berlin, Springer Nature Switzerland, Springer
• Erscheinungsjahr: 2025
• Sprache: Englisch
• ISBN-10: 3031967585
• ISBN-13: 9783031967580
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

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.

Von der hinteren Coverseite

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.