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

About the Author

Dr. Mohammad-Hassan Khooban is an Assistant Professor in the Department of Engineering and the Director of the Power Circuits and Systems Research Group at Aarhus University in Denmark. He has authored or co-authored more than 220 publications in peer-reviewed journals (mostly IEEE) and international conferences, written three book chapters, and holds one patent. He has been involved in six national and international projects. He was identified in 2019, 2020, and 2021 by Stanford University as one of the world’s top 2% researchers in engineering. He was also ranked 16th in the list of top 30 Electronics and Electrical Engineering Scientists in Denmark in 2022. His research interests include the application of advanced control, and optimization of artificial intelligence-inspired techniques in power electronics and systems.

"About this title" may belong to another edition of this title.

Store Description

I mainly carry imported books from South East Asia / South Asia for readers of all Age Groups.

Visit Seller's Storefront

Seller's business information

PLETOS INC
6931 51st Avenue, WOODSIDE, Woodside, NY, 11377, U.S.A.

Sale & Shipping Terms

Terms of Sale

We accept return for those books which are received damamged. Though we take appropriate care in packaing to avoid such situation.

Right of cancellation

Shipping Terms

Shipping rates within U.S.A.

Shipping rates within U.S.A.
Order quantity	12 to 19 business days	12 to 14 business days
First item	� 2.97	� 5.21

Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.