During the COVID-19 crisis period, when GDP growth became unusually volatile, the advantages of deep learning became even ...

As retail organizations navigate shifting consumer expectations and supply chain complexities, the role of data and ...

Researchers in China conceived a new PV forecasting approach that integrates causal convolution, recurrent structures, attention mechanisms, and the Kolmogorov–Arnold Network (KAN). Experimental ...

Numerous deep learning architectures have been developed to accommodate the diversity of time-series datasets across different domains. In this article, we survey common encoder and decoder designs ...