Metaheuristic and Machine Learning Optimization Strategies for Complex Systems

In contemporary engineering domains, optimization and decision-making issues are crucial. Given the vast amounts of available data, processing times and memory usage can be substantial. Developing and implementing novel heuristic algorithms is time-consuming, yet even minor improvements in solutions can significantly reduce computational costs. In such scenarios, the creation of heuristics and metaheuristic algorithms has proven advantageous. The convergence of machine learning and metaheuristic algorithms offers a promising approach to address these challenges. Metaheuristic and Machine Learning Optimization Strategies for Complex Systems covers all areas of comprehensive information about hyper-heuristic models, hybrid meta-heuristic models, nature-inspired computing models, and meta-heuristic models. The key contribution of this book is the construction of a hyper-heuristic approach for any general problem domain from a meta-heuristic algorithm. Covering topics such as cloud computing, internet of things, and performance evaluation, this book is an essential resource for researchers, postgraduate students, educators, data scientists, machine learning engineers, software developers and engineers, policy makers, and more. Title Page Copyright Page Book Series Table of Contents Detailed Table of Contents Preface Chapter 1: Experimental Investigation and Comparative Analysis of an Efficient Machine Learning Algorithm for Distribution System Reconfiguration Chapter 2: Integrated Approach for Network Intrusion Detection Chapter 3: Machine Learning for the Detection of Uniform Resource Locator Phishing Chapter 4: Machine Learning in Industrial IoT Applications for Safety, Security, Asset Localization, Quality Assurance, and Sustainability in Smart Production Chapter 5: Machine Learning in Industry IoT (IIoT) Chapter 6: Machine Learning in IoT for Smart Home Automation Chapter 7: Meta-Heuristics Algorithm for Computer Communications Chapter 8: Meta-Heuristic and Machine Learning Modelling and Optimizing Complex Systems Chapter 9: Meta-Heuristic Algorithms for Optimal Sizing of HRES Chapter 10: Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy Systems Chapter 11: Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy Systems Chapter 12: Metaheuristic Algorithms for Robot Path Planning Chapter 13: Meta-Heuristic Optimization for Enhanced Sensor-Based Health Monitoring in Cloud Computing Environments Chapter 14: Meta-Heuristics and Machine Learning Applications in Complex Systems Chapter 15: Metaheuristics and Machine Learning Convergence Chapter 16: Optimizing Optical Fiber Path in Wavelength Division Multiplexing Networks Using Particle Swarm Optimization Chapter 17: Performance Evaluation of Simulation-Driven Metaheuristic Algorithms Compilation of References About the Contributors Index