JIMÉNEZ NAVARRO , Manuel Jesús

La presente tesis se centra en el estudio de la predicción de series temporales mediante el uso de la técnica conocida como deep learning (aprendizaje profundo en español) o redes neuronales. A su vez, se realizan una serie de nuevas propuestas metodológicas, que mejoran la eficiencia de las arquitecturas existentes, aplicadas a una serie de...

Time series is one of the most common data types in the industry nowadays. Forecasting the future of a time series behavior can be useful in planning ahead, saving time, resources, and helping avoid undesired scenarios. To make the forecasting, historical data is utilized due to the causal nature of the time series. Several deep learning...

Ensuring the optimal performance of power transformers is a laborious task in which the insulation system plays a vital role in decreasing their deterioration. The insulation system uses insulating oil to control temperature, as high temperatures can reduce the lifetime of the transformers and lead to expensive maintenance. Deep...

The agricultural sector has been, and still is, the most important economic sector in many countries. Due to advances in technology, the amount and variety of available data have been increasing over the years. However, compared to other economic sectors, there is not always enough quality data for one particular domain (crops, plantations,...