Abstract: To optimize the dispatch of batteries, a model is required that can predict the state of energy (SOE) trajectory for a chosen open-loop power schedule to ensure admissibility (i.e., that ...

I have come across various ways of defining Artificial Neural Networks (ANNs). Many of them miss a fundamental characteristic of theirs. An ANN is a machine learning model. Like all machine learning ...

Neurointervention is a highly specialized area of medicine and, as such, neurointerventional research studies are often more challenging to conduct, require large, multicenter efforts and longer study ...

The study is useful for advancing spatial transcriptomics through its novel regression-based linear model (glmSMA) that integrates single-cell RNA-seq with spatial reference atlases, and its ...

Abstract: This article presents an inverse optimal control (IOC) approach for nonlinear polynomial systems based on adaptive dynamic programming (ADP). First, a novel model-based algorithm is ...