Air Transport: A Computer Science Perspective

個数:1
紙書籍版価格
¥29,841
  • 電子書籍
  • ポイントキャンペーン

Air Transport: A Computer Science Perspective

  • 著者名:Wandelt, Sebastian/Sun, Xiaoqian
  • 価格 ¥25,179 (本体¥22,890)
  • Elsevier(2025/10/14発売)
  • 2025→2026年!Kinoppy電子書籍・電子洋書全点ポイント30倍キャンペーン(~1/1)
  • ポイント 6,840pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9780443451508
  • eISBN:9780443451515

ファイル: /

Description

Air Transport: A Computer Science Perspective examines the integration of computer science principles in air transportation, bridging the gap between theory and real-world applications. It delves into automation, problem solving, and innovative aviation technologies. Authored by a seasoned team of a computer scientist and an airspace engineer, it offers a unique blend of expertise that highlights practical algorithms, data structures, and optimization techniques essential for flight operations and autonomous systems. Readers will learn about the latest regulations, ensuring they are well-equipped to navigate the evolving air transport landscape.Structured in five parts, the book begins with foundational concepts like computational complexity and intelligence. It then explores airline operations, including network design, flight scheduling, fleet assignment, and aircraft routing. The exploration continues with airport operations, focusing on gate assignment, ground vehicle allocation, and delay prediction. In the realm of air traffic flow management, readers will discover trajectory optimization, airspace sectorization, and network resilience assessment. The final section summarizes key insights and future trends.This book is an invaluable resource for transportation engineers, computer scientists, and professionals in data science, software engineering, and aviation research. It is ideal for students in aerospace engineering, computer science, and data science programs, emphasizing practical applications that drive innovation and efficiency in the air transport sector.- Provides expert reviews of the latest research, emphasizing applications in air transport- Focuses on applying machine learning, deep learning, and optimization algorithms for innovative air transport solutions- Includes practical strategies for managing algorithm efficiency, scalability, and complexity-accuracy trade-offs in real-world scenarios

Table of Contents

PART 1 Foundations1. Introduction2. Computational Complexity3. Computational IntelligencePART 2 Airlines Operations4. Network Design5. Flight Scheduling6. Fleet Assignment7. Aircraft Routing8. Crew schedulingPART 3 Airport Operations9. Gate Assignment10. Ground Vehicle Allocation11. Delay PredictionPART 4 Air Traffic Flow Management12. Trajectory Optimization13. Airspace Sectorization14. Network Resilience AssessmentPART 5 Conclusions15. Summary and Outlook

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