Comparing ensemble learning algorithms and severity of illness scoring systems in cardiac intensive care units: a retrospective study ...

This paper introduces an innovative Adaptive Stacking Ensemble Model (ASEM) that incorporates Genetic Algorithm-based Hyper-parameter optimization to predict the SOH of lithium-ion batteries. ASEM ...

Researchers from Yandex and HSE University introduced a model named TabM, built upon an MLP foundation but enhanced with BatchEnsemble for parameter-efficient ensembling. This model generates multiple ...

Multidomain proteins with long flexible linkers and full-length intrinsically disordered proteins (IDPs) are best defined as an ensemble of conformations rather than a single structure. Determining ...

The resource scheduling model converges to the optimal solution using a novel many-objective ensemble optimization algorithm based on a dynamic selection mechanism. The study also explores the support ...

To boost the performance of the proposed ensemble model, the outputs of each model are optimally weighted to form the final prediction output. The ensemble models’ weights are optimized in terms of a ...

In this study, a conjunction model, EEMD-SSA-LSTM for short, which comprises ensemble empirical mode decomposition (EEMD) and sparrow search algorithm (SSA)–based long short-term neural networks (LSTM ...