Meta-Heuristics and Machine Learning Applications in Complex Systems
A. Ponmalar, Kallur V. Vijayakumar, C. Lakshmipriya, M. Karthikeyan, Gracelin Sheena B., P. J. Beslin Pajila, Siva Subramanian R · Advances in systems analysis, software engineering, and high performance computing book series · 2024
In order to understand and optimise complex systems, this work explores the synergy between machine learning (ML) and meta-heuristic techniques. It investigates how problems in a variety of industries, including computer communications, renewable energy, power systems, machining, and cloud computing, may be solved by fusing machine learning (ML) with intelligent algorithms derived from natural processes. Comprehensive discussions include subjects such as improving thermal performance in solar devices, sizing renewable energy systems, and optimising power distribution and machining processes. It also explores on hybrid methods, which combine machine learning (ML) and meta-heuristics for better optimisation, as well as the convergence of ML with the industrial internet of things (IIOT). For scholars, and professionals, the research be insightful information along with a thorough summary and future directions in this multidisciplinary field.