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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
PHILNet: A novel efficient approach for time series forecasting using deep learning
(ScienceDirect, 2023)
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. ...
Artículo
A Bayesian Optimization-Based LSTM Model for Wind Power Forecasting in the Adama District, Ethiopia
(MDPI, 2023-02)
Renewable energies, such as solar and wind power, have become promising sources of energy to address the increase in greenhouse gases caused by the use of fossil fuels and to resolve the current energy crisis. Integrating ...
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, ...