Titlebook: Spotlight on Modern Transformer Design; Pavlos S. Georgilakis Book 2009 Springer-Verlag London 2009 artificial intelligence.classification

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Anthem

Spotlight on Modern Transformer Design978-1-84882-667-0Series ISSN 1612-1287 Series E-ISSN 1860-4676

皮萨

exophthalmos

Free-Radical

Evaluation of Transformer Technical Characteristicse noload loss classification problem. Artificial neural networks are used to solve the no-load loss prediction problem. Impedance voltage evaluation is implemented using a particular finite element model with detailed representation of winding geometry.

MAZE

Transformer Selectionla and it also introduces the external environmental cost due to transformer losses. Using the methodologies of this chapter, transformer users will save money by purchasing the most cost-effective and energy-efficient transformers.

Germinate

Pavlos S. GeorgilakisThe first book to introduce artificial intelligence to transformer design.Includes supplementary material:

Fibrinogen

Transformerst are typically used for transformer manufacturing. It presents the type, routine, and special tests that are performed on transformers. It classifies transformers according to their use, cooling medium, insulating medium, and core construction. Finally, this chapter describes the type and characteristics of transformers studied in this book.

conduct

minimal