Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models

This book explores recent advancements in fuzzy theory and performance prediction for queuing and reliability models, focusing on their application in engineering systems like call centers and manufacturing. It serves researchers and students alike.

Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models explores the latest advancements in fuzzy theory and performance prediction within the realms of queuing and reliability models. The book employs stochastic modeling and optimization theory to analyze and enhance the performance of real-time engineering systems, such as call centers, telecommunications, and manufacturing processes. It emphasizes the integration of fuzzy logic with queuing and reliability theory to improve decision-making in various industrial and everyday scenarios.

Throughout its twenty chapters, the book delves into both theoretical frameworks and practical applications of fuzzy logic, reliability, and queuing models. It covers a wide array of topics relevant to researchers, educators, and undergraduate students in fields such as Engineering, Business Management, and Mathematical Sciences. Each chapter presents insights into performance measures and effectiveness, equipping readers with the tools necessary for optimal design and analysis of complex systems.

By assessing various performance metrics, the book provides valuable guidance for addressing queuing situations and predicting the reliability of components within computer, communication, and manufacturing systems. This comprehensive examination not only highlights recent breakthroughs but also serves as a resource for those looking to enhance their understanding of analytics in engineering contexts. Overall, it is a significant contribution to the fields of fuzzy theory and performance prediction, offering a blend of theoretical knowledge and practical insights.