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Нейромережеве моделювання критичних температур піттінгоутворення сталі

Published in Реєстрація зберігання і обробка даних • Mar 19, 2019
NobleIDNI2P23W17R51S87
Authors:
О. В. Корнієнко
,
S. O. Subbotin
,
O. E. Naryvskyi

Abstract

The task of creating mathematical software for constructing quantitative dependency models based on forward propagation neural networks has been solved in the work. A modification of method for dropping out neurons is proposed, which better prevents the model from overfitting. The modified method ta...

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