Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...

Abstract: Federated Learning (FL) is an emerging computing paradigm to collaboratively train Machine Learning (ML) models across multi-source data while preserving privacy. The major challenge of ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Researchers at Central South University in China have developed a new model to improve ultra-short-term photovoltaic (PV) power prediction, as detailed in their publication in Frontiers in Energy. In ...

ABSTRACT: Accurate prediction of survey response rates is essential for optimizing survey design and ensuring high-quality data collection. Traditional methods often struggle to capture the complexity ...

Mood swings in reproductive-age women arise from interacting hormonal, metabolic, and lifestyle factors, yet scalable screening tools remain limited. Artificial intelligence (AI) and machine learning ...

Henry Krumb School of Mines, Earth and Environmental Engineering Department, Columbia University, New York, New York 10027, United States ...

Abstract: With the continuous development of artificial intelligence technology, its application has gradually penetrated into the field of psychiatry, especially in the early prediction and auxiliary ...