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Table of contents (13 chapters)
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Front Matter
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Introduction
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Automatic Learning Methods
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Front Matter
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Application of Automatic Learning to Security Assessment
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Front Matter
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Automatic Learning Applications in Power Systems
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Front Matter
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Back Matter
Keywords
About this book
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.
Automatic Learning Techniques in Power Systems is a useful reference source for professionals and researchers developing automatic learning systems in the electrical power field.
Authors and Affiliations
Bibliographic Information
Book Title: Automatic Learning Techniques in Power Systems
Authors: Louis A. Wehenkel
Series Title: Power Electronics and Power Systems
DOI: https://doi.org/10.1007/978-1-4615-5451-6
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 1998
Hardcover ISBN: 978-0-7923-8068-9Published: 30 November 1997
Softcover ISBN: 978-1-4613-7489-3Published: 14 October 2012
eBook ISBN: 978-1-4615-5451-6Published: 06 December 2012
Series ISSN: 2196-3185
Series E-ISSN: 2196-3193
Edition Number: 1
Number of Pages: XXIX, 280
Topics: Electrical Engineering, Artificial Intelligence, Natural Language Processing (NLP)