C&EN

A Simple and Scalable Kernel Density Approach for Reliable Uncertainty Quantification in Atomistic Machine Learning

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator.
IEEE

Probabilistic Interval State Estimation for Distribution System With Correlation Probability Box Depicting Stochastic Uncertainties of DG

Abstract: Stochastic uncertainty, comprising both aleatory and epistemic uncertainties, is intrinsic in the distributed generation (DG). However, existing distribution system state estimation (DSSE) ...
IEEE

The Density Peaks Clustering Algorithm Based on a Combination of Polynomial Kernel and EP Kernel with K-Nearest Neighbors

Abstract: To address the problem of inaccurate cluster center selection in the Density Peaks Clustering (DPC) algorithm when applied to datasets with non-uniform density distributions, this paper ...
Frontiers

Stroke rate–stroke length dynamics in elite freestyle swimming: application of kernel density estimation

Objectives: To analyse stroke rate (SR) and stroke length (SL) combinations among elite swimmers to better understand stroke strategies across all race distances of freestyle events. Design: We ...