By Topic

Spotlight on transformer design

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Pavlos S. Georgilakis ; Dept. of Production Eng. & Manage., Tech. Univ. Crete, Chania ; Eleftherios I. Amoiralis

This paper presents an integrated artificial intelligence technique to achieve an optimum design of a transformer. AI is used to reach an optimum transformer design solution for the winding material selection problem. To be more precise, decision trees (DTs) and adaptive trained neural networks (ATNNs) are combined with the aim of selecting the appropriate winding material (Cu or Al) to design an optimum distribution transformer. Both methodologies have emerged as important tools for classification

Published in:

IEEE Power and Energy Magazine  (Volume:5 ,  Issue: 1 )