Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...
Traditional lending relies on collateral and a financial history that productive smallholder farmers may find difficult to ...
Curious about how to secure renewable-dominant power systems? A team from Shandong University developed a method combining GBDT and FP-Growth algorithms. It quickly assesses cascading failure risks, ...
Balancing nitrogen use is critical for maximizing crop yield while minimizing environmental and economic costs.
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 ...
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 ...
Abstract: This research aims to formulate an optimal control algorithm for a hydrothermal air-conditioning system, with the objective of minimizing energy consumption while simultaneously ensuring ...
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