Reliability and Statistics in Transportation and Communication

This book reports on cutting-edge theories and methods for analyzing complex systems, such as transportation and communication networks, and discusses multi-disciplinary approaches to dependability problems encountered in practice. It presents the most relevant findings discussed at the 22nd International Multidisciplinary Conference on Reliability and Statistics in Transportation and Communication (RelStat), which took place in Riga, Latvia, in hybrid mode, with a special emphasis on the integration of artificial intelligent concepts into reliability approaches.

Format: Paperback / softback
Length: 540 pages
Publication date: 21 February 2023
Publisher: Springer International Publishing AG

This comprehensive book delves into cutting-edge theories and methodologies for analyzing complex systems, encompassing transportation and communication networks, while also exploring multidisciplinary approaches to addressing reliability challenges in practical settings. Presented at the 22nd International Multidisciplinary Conference on Reliability and Statistics in Transportation and Communication (RelStat), held in Riga, Latvia, from October 20 to 21, 2022, in a hybrid format, the book showcases the most significant findings discussed during the conference. Spanning a wide range of advanced theories and methods, it places particular emphasis on integrating artificial intelligence concepts into reliability frameworks.

The book begins by introducing the fundamental principles and concepts of complex systems analysis, providing a solid foundation for the subsequent chapters. It then delves into advanced theories and methods, such as network modeling, simulation, and optimization, which are employed to understand the behavior and performance of complex systems.

One of the key themes of the book is the integration of artificial intelligence concepts into reliability approaches. The authors discuss how AI algorithms can be used to analyze large datasets, identify patterns, and make predictions, which can help improve the reliability of complex systems. They also explore how AI can be used to develop new reliability models and optimize existing ones, leading to more efficient and effective decision-making processes.

Another important aspect of the book is the discussion of multidisciplinary approaches to reliability problems. The authors recognize that complex systems often involve multiple disciplines, such as engineering, mathematics, and computer science, and that a holistic approach is necessary to address their challenges effectively. They discuss how different disciplines can collaborate and contribute to the development of new theories and methods, leading to more comprehensive and effective solutions.

Throughout the book, real-world examples and case studies are used to illustrate the practical applications of the discussed theories and methods. These examples help to demonstrate the importance of the discussed concepts and provide insights into the challenges and opportunities associated with analyzing and improving complex systems.

In conclusion, this book is a valuable resource for researchers, practitioners, and students interested in analyzing complex systems and addressing reliability challenges. It provides a comprehensive overview of the latest theories and methods, while also emphasizing the importance of interdisciplinary approaches and the integration of artificial intelligence concepts into reliability frameworks. By presenting the most relevant findings discussed at the 22nd International Multidisciplinary Conference on Reliability and Statistics in Transportation and Communication, the book offers valuable insights into the future of complex systems analysis and management.

Weight: 842g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031266546
Edition number: 1st ed. 2023