Control Strategy for Time-Delay Systems
Mohammad-Hassan Khooban, Tomislav Dragicevic
Häftad, 2020
1 939 kr
Applications of Deep Machine Learning in Future Energy Systems
Häftad, Engelska, 2024
2 299 kr
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Applications of Deep Machine Learning in Future Energy Systems pushes the limits of current Artificial Intelligence techniques to present deep machine learning suitable for the complexity of sustainable energy systems. The first two chapters take the reader through the latest trends in power engineering and system design and operation before laying out current AI approaches and limitations. Later chapters provide in-depth accounts of specific challenges and the use of innovative third-generation machine learning, including neuromorphic computing, to resolve issues from security to power supply.
An essential tool for the management, control, and modelling of future energy systems, this book maps a practical path towards AI capable of supporting sustainable energy.
- Clarifies the current state and future trends of energy system machine learning and the pitfalls facing our transitioning systems
- Provides guidance on 3rd-generation AI tools for meeting the challenges of modeling and control in modern energy systems
- Includes case studies and practical examples of potential applications to inspire and inform researchers and industry developers
Produktinformation
- Utgivningsdatum2024-08-21
- Mått152 x 229 x 18 mm
- Vikt450 g
- FormatHäftad
- SpråkEngelska
- Antal sidor334
- FörlagElsevier Science
- ISBN9780443214325
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Control Strategy for Time-Delay Systems
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