Aquila-optimized XGBoost improves reinforced subgrade strength predictions
An Aquila-optimized XGBoost model achieved an R² of 0.980 for predicting soaked CBR in 90 geosynthetic-reinforced subgrade tests, outperforming three ...
An Aquila-optimized XGBoost model achieved an R² of 0.980 for predicting soaked CBR in 90 geosynthetic-reinforced subgrade tests, outperforming three ...
A new adaptive hybrid forecasting framework that dynamically reweights ARIMA, SETAR, and neural network components, augmented with a GARCH volatility ...
Researchers in Iran combined Sentinel-2 satellite data, hybrid machine learning, and game theory to rank groundwater quality parameters, finding that ...
Researchers have built a hybrid quantum-classical deep learning model that uses variational quantum circuits and a statistical image prior to ...
A new bibliometric analysis of 961 publications shows that AI research in psychology has shifted after 2023 from technical themes ...
Researchers have developed FedHybrid-ViT, a privacy-preserving framework that fuses convolutional and transformer models within federated learning to detect deepfakes across ...
A 25-year review of artificial intelligence applications in streamflow forecasting reveals that feed-forward neural networks dominate the field while long-range ...
A 38-year machine learning study in Mymensingh, Bangladesh, shows LSTM networks forecast daily minimum temperatures with high accuracy but detect ...
© 2025 Scienmag - Science Magazine
© 2025 Scienmag - Science Magazine