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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