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Machine Learning-Based Techniques for False Data Injection Attacks Detection in Smart Grid: A Review by Benras Mohamed Tahar; Sid Mohamed Amine; Oussama Hachana is a book available to read on EtoBox.

What is Machine Learning-Based Techniques for False Data Injection Attacks Detection in Smart Grid: A Review about?

In this book, one hundred selected articles, in which the technology and science elite share, contribute to technology development, collaborate and evolve the latest cutting-edge technologies, open ecosystem resources, new innovative computing solutions, hands-on labs and tutorials, networking and community building, to ensure better integration of artificial intelligence into renewable energy systems. Innovation in computing continues at a growing pace. The key to success in this area is not only hardware, but also the ability to leverage rapid advances in artificial intelligence (including machine learning and deep learning), data analytics, data streaming, and cloud computing, which go hand in hand with intensive research activity on the underlying computational methods. The chapters in this book are organized into thematic sections on: advanced computing techniques; artificial intelligence; smart and sustainable cities; renewable energy systems; materials in renewable energy; smart energy efficiency; smart cities applications: recent developments and new trends; online, supervision of renewable energy platforms; predictive control in renewable systems; smart embedded systems fo

Author

Benras Mohamed Tahar; Sid Mohamed Amine; Oussama Hachana

Publisher

Springer International Publishing Springer

Published

2023

Language

EN

ISBN

9783031212154

Subjects

Science, Stem