Explainable AI Model Hits 98.92% Accuracy in Predicting Student Readiness for Industry 4.0 Careers
Researchers in China have built an explainable AI framework that predicts student readiness for Industry 4.0 careers with 98.92 percent ...
Researchers in China have built an explainable AI framework that predicts student readiness for Industry 4.0 careers with 98.92 percent ...
A deep learning model trained on 45 years of Nigerian weather data predicts heatwave trends in the country's northwest with ...
Researchers have built a federated, explainable VAE-LSTM framework that detects previously unseen DDoS attacks in software-defined healthcare networks with over ...
Researchers in Shanghai have developed a deep reinforcement learning framework that coordinates edge caching across multiple nodes in smart industrial ...
A new LSTM-based dataset called MemoryFlux maps two decades of net ecosystem CO2 exchange across North America with unprecedented fidelity, ...
A Norwegian study shows that a deep learning LSTM network outperforms the country's operational HBV model in simulating both snowmelt- ...
Researchers at the University of Port Harcourt combined Random Forest, LSTM, Prophet, and XGBoost stacking with DeepSeek-R1 cognitive analysis to ...
A new dendrite-inspired recurrent neural network architecture outperforms LSTMs on chaotic forecasting benchmarks and achieves strong seizure detection in raw ...
A 43-year, 38-station machine-learning study of Nigerian rainfall identifies four shifting climate zones, rising monsoon extremes and last-month rainfall as ...
Researchers have built a microgrid scheduling system that pairs online electric vehicle battery state estimation with a neural network surrogate, ...
© 2026 Scienmag - Science Magazine
© 2026 Scienmag - Science Magazine