by Mohammad-Hassan Khooban (Editor)
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.
Delivery time | Instant download |
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Year | 2024 |
Pages | 329 |
Language | English |
Format | |
Size | 28 MB |
ASIN | B0DF52NXMZ |
ISBN-10 | 0443214328, 044321431X |
ISBN-13 | 9780443214325, 978-0443214325, 978-0-443-21432-5, 9780443214318, 978-0443214318 |