Data-driven prediction of time series is significant in many scientific research fields such as global climate change and weather forecast. For global monthly mean temperature series, considering t…
This paper proposes two hybrid approaches based on Autoencoders (AEs) for long-term temperature prediction. The first algorithm comprises an AE trained to learn temperature patterns, which is then …
Solute artificial neural network geothermometers offer the possibility to overcome the complexity given by the solute-mineral composition. Herein, we present a new concept, trained from high-qualit…