Tag: GRU

A twelve-year empirical study of China's A-share equity market shows that deep learning models such as LSTMs and Transformers outperform ...

A study in Energy Informatics shows that incorporating temporal load-history information significantly improves the accuracy of short-term HVAC load forecasting ...

Researchers have developed a lag-informed deep-learning framework that delivers 10-hour-ahead downstream water-level forecasts in Sri Lanka's flood-prone Kalu Ganga Basin.

A new GRU–TimeMixerKAN deep learning model achieved the lowest prediction errors across three reactivated landslides in China's Three Gorges Reservoir ...

A dual-confirmation framework combining partial lag correlation matrices and Granger causality improved multi-region electricity load forecasting in 25 of 54 ...

A retrospective multicentre study reports that a deep learning model combining three time-point chest CT scans predicted MDR-TB treatment outcomes ...

Researchers have built a two-stage deep learning system in which a transformer makes an initial electricity demand forecast and an ...

Researchers in Kazakhstan have developed a two-stage deep learning method that forecasts the solar spectrum itself and uses it to ...

Researchers in India built a transformer-based deep learning system to detect anomalies in solar-wind power plants, achieving strong reconstruction accuracy ...

A systematic review and controlled validation of deep learning-based Android malware detection reveals that high benchmark accuracy masks architecture-dependent reliability ...