Discovering new drugs is a complicated, time-consuming, costly, risky and failure-prone process. However, about 80% of the drugs that have been approved so far are targeted at protein targets, and 99% ...
Researchers in China have applied a machine learning technology based on temporal convolutional networks in PV power forecasting for the first time. The new model reportedly outperforms similar models ...
Researchers have developed a novel deep-learning method to predict ultra-short-term PV power, using an optimization method that is based on the behavior of dung beetles. The proposed approach ...
Economists from HSE University have developed a neural network model that can predict the onset of a short-term stock market crisis with over 83% accuracy, one day in advance. The model performs well ...
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AI maps heat inside steelmaking’s critical sintering process beds
The Temporal Fusion Transformer model provides near-real-time insights into sintering temperatures, addressing critical ...
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