Machine Learning Predictive Analytics And Optimization In Complex Systems
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Machine Learning, Predictive Analytics, and Optimization in Complex Systems
Author: John Joseph, Ferdin Joe
language: en
Publisher: IGI Global
Release Date: 2025-06-27
The integration of machine learning, predictive analytics, and optimization techniques revolutionizes the understanding and management of complex systems. From supply chains and energy grids to healthcare and financial markets, these systems are characterized by dynamic interactions, uncertainty, and large data amounts. Machine learning enables insights into data patterns, analytics predict future behaviors, and optimization methods guide decision-making. When combined, these tools offer solutions for enhancing system performance, resilience, and adaptability. As complexity grows, their collaboration becomes vital for creating intelligent, responsive, and sustainable systems. Machine Learning, Predictive Analytics, and Optimization in Complex Systems examines the integration of intelligent technologies into system design and management, and data analysis. It explores strategies for data-informed decisions, intelligent technology utilization, and security optimization. This book covers topics such as computer engineering, smart ecosystems, and system design, and is a useful resource for computer engineers, data analysts, academicians, researchers, and scientists.
Optimization in Machine Learning and Applications
This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.
Reliability Analysis and Maintenance Optimization of Complex Systems
This book is a comprehensive guide to methodologies for analyzing reliability and optimizing maintenance in complex systems, spanning from initial design to operational stages. The book comprises 20 chapters, each addressing different research topics in the reliability and maintenance of complex systems. These chapters are authored by esteemed professors and researchers in the field of reliability engineering, and they are organized as follows: System Reliability Modeling (8 chapters), Optimal Maintenance Models (4 chapters), System Performance and Availability Analysis (3 chapters), and Reliability Testing and Accelerated Life Tests (2 chapters). The remaining chapters focus on reliability testing and life data analysis. The book offers an in-depth exploration of various techniques, algorithms, and practical industry applications, making it an invaluable resource for researchers engaged in system reliability analysis and maintenance optimization, as well as for practical engineers and industrial managers. This book will be useful to students, researchers, and engineers in understanding the latest research issues and techniques in reliability and maintenance engineering.