Real-time seismic intensity prediction using self-supervised contrastive gnn for earthquake early warning
Seismic intensity prediction from early or initial seismic waves received by a few seismic
stations can enhance earthquake early warning systems (EEWSs), particularly in ground …
stations can enhance earthquake early warning systems (EEWSs), particularly in ground …
SolarNet-An efficient multi-model ensemble approach for Solar Power Forecasting based on Artificial Intelligence
Solar energy has become a critical topic in the field of electrical power generation, and it is
expected to remain so soon due to the world's finite supply of fossil fuels and experts' …
expected to remain so soon due to the world's finite supply of fossil fuels and experts' …
HsNet–Enhancing Cardiovascular Health Detection through Advanced Signal Processing and Machine Learning
Phonocardiogram (PCG) signals offer a crucial indicator of cardiac health. Our research
aims to accurately classify heart sounds for robust cardiovascular health assessment …
aims to accurately classify heart sounds for robust cardiovascular health assessment …
SpectroSzNet: Deep Learning-Based Enhancement for Schizophrenia Classification Using Spectrograms
Schizophrenia is a neuropsychiatric disorder characterized by delusions, auditory
hallucinations, mood swings, and unusual behavior. Early detection of Schizophrenia can …
hallucinations, mood swings, and unusual behavior. Early detection of Schizophrenia can …
SmartChargeNet: PCA-Enhanced Attention-LSTM for Wireless Electric Vehicle Charging Optimization
Wireless charging for electric vehicles (EVs) has gained significant popularity due to its
contactless nature, eliminating the need for physical connections between the transmitter …
contactless nature, eliminating the need for physical connections between the transmitter …