Automatic Learning Techniques in Power Systems

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Automatic Learning Techniques in Power Systems is dedicated to the practical application of automatic learning to power systems. Power systems to which automatic learning can be applied are screened and the complementary aspects of automatic learning, with respect to analytical methods and numerical simulation, are investigated.

This book presents a representative subset of automatic learning methods - basic and more sophisticated ones - available from statistics both classical and modern , and from artificial intelligence both hard and soft computing. The text also discusses appropriate methodologies for combining these methods to make the best use of available data in the context of real-life problems.

Deep Learning is Large Neural Networks

Automatic Learning Techniques in Power Systems is a useful reference source for professionals and researchers developing automatic learning systems in the electrical power field. JavaScript is currently disabled, this site works much better if you enable JavaScript in your browser. Buy eBook. View Product.

Aleksei Zhukov - Google Scholar Citations

Debugging Systems-on-Chip: Communication-centric and. This book describes an approach and supporting infrastructure to facilitate debugging the silicon implementation of This book describes an approach and supporting infrastructure to facilitate debugging the silicon implementation of a System-on-Chip SOC , allowing its associated product to be introduced into the market more quickly.

Readers learn step-by-step the key requirements for debugging a modern, silicon Discrete Event Systems: Analysis and Control. This book provides a survey of the current state of the art in the Electrophysiology of the Central Nervous System.


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  4. Description Table of Contents Product Details Click on the cover image above to read some pages of this book! All Rights Reserved. In Stock.

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