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Artículo
An Experimental Review on Deep Learning Architectures for Time Series Forecasting
(World Scientific, 2021)
In recent years, deep learning techniques have outperformed traditional models in many machine learning tasks. Deep neural networks have successfully been applied to address time series forecasting problems, which is a ...
Artículo
An evolutionary algorithm to discover quantitative association rules in multidimensional time series
(Springer, 2011)
An evolutionary approach for finding existing relationships among several variables of a multidimensional time series is presented in this work. The proposed model to discover these relationships is based on quantitative ...
Artículo
Recent Advances in Energy Time Series Forecasting
(MDPI, 2017)
This editorial summarizes the performance of the special issue entitled Energy Time Series Forecasting, which was published in MDPI’s Energies journal. The special issue took place in 2016 and accepted a total of 21 ...
Artículo
Data streams classification using deep learning under different speeds and drifts
(Oxford University Press, 2022)
Processing data streams arriving at high speed requires the development of models that can provide fast and accurate predictions. Although deep neural networks are the state-of-the-art for many machine learning tasks, ...
Artículo
Short-term solar irradiance forecasting in streaming with deep learning
(Elsevier, 2023)
Solar energy is one of the most common and promising sources of renewable energy. In photovoltaic (PV) systems, operators can benefit from future solar irradiance predictions for efficient load balancing and grid stability. ...