Applications of Deep Machine Learning in Future Energy Systems
Author:Mohammad-Hassan Khooban (Editor)
Publisher finelybook 出版社:Elsevier
Edition 版本:1st edition
Publication Date 出版日期:2024-09-4
Language 语言:English
Print Length 页数:334pages
ISBN-10:0443214328
ISBN-13:9780443214325
Book Description
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
Review
From the Back Cover
The first two chapters take the reader through the latest trends in power engineering and system design and operation, before laying out the current AI approaches and our outstanding 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, Applications of Deep Machine Learning maps a practical path towards AI capable of supporting sustainable energy.