Artificial Intelligence and System Engineering

Radek Silhavy

ISBN 10: 3031967585 / ISBN 13: 9783031967580

Published by Springer, Berlin, Springer Nature Switzerland, Springer, 2025

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -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. 593 pp. Englisch.

Seller Inventory # 9783031967580

Bibliographic Details

• Title: Artificial Intelligence and System Engineering
• Publisher: Springer, Berlin, Springer Nature Switzerland, Springer
• Publication Date: 2025
• Language: English
• ISBN 10: 3031967585
• ISBN 13: 9783031967580
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 33D millimeters 235 millimeters width by 155 millimeters height by 33 millimeters depth
• Weight: 914 grams

About this title

Synopsis

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.