This study proposes a hybrid modeling approach that integrates a Physics Informed Neural Network (PINN) and a long short-term memory (LSTM) network to predict river water temperature in a defined ...

Abstract: A novel forecasting model of the bidirectional LSTM with self-attention (Bi-LSTM-SA) is introduced to address the need to upgrade the accurate projection of electrical load forecasting. The ...

Irregular waves exhibit complex and erratic behavior, posing significant challenges for accurate short-term ship motion forecasting. Reliable ship navigation depends on precise motion predictions, ...

Abstract: To improve the low accuracy of the SGP4 model in short-term orbit prediction for medium Earth orbit satellites and the instability in LSTM model training, this paper proposes and develops an ...

Mesoscale eddies are the most important mesoscale phenomena in the oceans, and determining how to predict their spatial and temporal characteristics is a very challenging task. Most previous studies ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Batch reactors are type of chemical reactors, where the reactants are loaded to ...

The National Oceanic and Atmospheric Administration reports a 95% decline in the oldest Arctic ice over the last 33 years [1], while the National Aeronautics and Space Administration states that ...

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are ...