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Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm

Foundations, Methods, and Applications

Jezik AngleščinaAngleščina
Knjiga Mehka
Knjiga Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm Mohd Herwan Sulaiman
Koda Libristo: 48721922
Založba Elsevier Science, november 2025
Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm: F... Celoten opis
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Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm: Foundations, Methods, and Applications reveals the potential of innovative optimization algorithms to support sustainability in modern energy systems. This book provides a multidisciplinary foundation for the reader, with Part I breaking down fundamentals including the challenges to be addressed in renewable energy systems and detailed methodologies including swarm-, physics-, and human-based algorithms, before introducing the Barnacles Mating Optimizer and Evolutionary Mating Algorithm themselves. Part II drills deeper into examples, case studies, and applications for energy systems, offering comparative analysis with alternative tools, and providing complimentary MATLAB code using the latest Toolbox. A sandbox for readers to learn, skill-build, and develop in, ‘Intelligent Energy Systems using BMO and EMA’ provides an indispensable guide to these cutting-edge AI tools for new and experienced readers.

  • Builds step-by-step from foundational principles to complex applications in sustainable energy systems
  • Includes case studies, tools, and complimentary MATLAB code to try out, rework, and apply to new problems
  • Guides readers through these innovative methods, as part of the ground-breaking Advances in Intelligent Energy Systems

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O knjigi

Polni naslov Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm
Jezik Angleščina
Vezava Knjiga - Mehka
Datum izida 2025
Število strani 250
EAN 9780443337758
ISBN 0443337756
Koda Libristo 48721922
Založba Elsevier Science
Teža 450
Mere 152 x 229
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