Neural network modeling of critical tempe-ratures for steel pitting.

• Дата: 2019
• Автори: Korniienko, O. V., Subbotin, S. O., Naryvskyi, O. E.
• Формат: Стаття
• Мова: Українська
• Опубліковано: Інститут проблем реєстрації інформації НАН України 2019
• Теми: dataset; training; neural network; error; gradient; dropout; probability; AiSi 321 steel
• Онлайн доступ: http://drsp.ipri.kiev.ua/article/view/179699
• Назва журналу: Data Recording, Storage & Processing

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...