Neural network modeling of critical tempe-ratures for steel pitting.
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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Datum: | 2019 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | Ukrainian |
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Інститут проблем реєстрації інформації НАН України
2019
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Online Zugang: | http://drsp.ipri.kiev.ua/article/view/179699 |
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Назва журналу: | Data Recording, Storage & Processing |