Unsupervised neural method for temperature forecasting
Fecha de publicación
Artificial Intelligence in Engineering. Volumen 13 (4), pp. 351-357. Elsevier BV.
This article presents the results of using a novel Negative Feedback Artificial Neural Network for extraction of models of the thermal structure of oceanographic water masses and to forecast time series in real time. The results obtained using this model are compared with those obtained using a Linear Regression and an ARIMA model. The article presents the Negative Feedback Artificial Neural Network, shows how it extracts the model behind the data set and discuses the Artificial Neural Network's forecasting abilities.
- Untitled