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Math. Comput. Appl. 2003, 8(2), 201-208; doi:10.3390/mca8020201

Neural Network Using Genetic Algorithm for Magnetic Performance Prediction of Toroidal Wound Cores at 50 Hz

Uludag University, Arts and Sciences Faculty, Physics Department, 16059 Gorukle-Bursa, Turkey
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Published: 1 August 2003
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Abstract

Geometrical and building parameters have a strong influence on magnetic performance of toroidal wound cores made from grain oriented 3% SiFe electrical steel. From a sample of 40 cores with dimensions ranging from 35 to 160 mm outer diameter, 25 to 100 mm inner diameter and JO to 70 mm strip width and a flux density range of 0.1 to 1.7 T have been obtained and used as training data to a generalised feedforward neural network.
Keywords: Artificial neural network; Genetic algorithm; toroidal wound core; magnetic performance Artificial neural network; Genetic algorithm; toroidal wound core; magnetic performance
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Kucuk, I.; Derebasi, N. Neural Network Using Genetic Algorithm for Magnetic Performance Prediction of Toroidal Wound Cores at 50 Hz. Math. Comput. Appl. 2003, 8, 201-208.

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