Resumen
The steepest descent method is frequently used for neural network tuning. Mini-batches are commonly used to get better tuning of the steepest descent in the neural network. Nevertheless, steepest descent with mini-batches could be delayed in reaching a minimum. The Hessian could be quicker than the steepest descent in reaching a minimum, and it is easier to achieve this goal by using the Hessian with mini-batches. In this article, the Hessian is combined with mini-batches for neural network tuning. The discussed algorithm is applied for electrical demand prediction.
Idioma original | Inglés |
---|---|
Número de artículo | 2036 |
Publicación | Applied Sciences (Switzerland) |
Volumen | 10 |
N.º | 6 |
DOI | |
Estado | Publicada - 1 mar. 2020 |