Results 221 to 230 of about 1,160,391 (297)

Monte Carlo simulations of optical propagation in human skin using experimentally measured laser parameters. [PDF]

Lasers Med Sci
Girasol CE, Lobão RMQ, Sampaio MS, Cruz-Junior LB, Guirro RRJ, Bachmann L.   +5 more
europepmc   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Monte Carlo-based Design and Comparative Evaluation of Intraoperative Radiotherapy Disks. [PDF]

J Med Phys
Bagheri M, Al Shareefi HH.
europepmc   +1 more source

Enhancing quasi-Monte Carlo methods via delta dimension and directional control technique

core  

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Search model based on Kalman Filter and Monte Carlo simulation. [PDF]

PLoS One
Liu J, Li Y, Liu X.
europepmc   +1 more source

Monte Carlo and Kinetic Monte Carlo Methods A Tutorial

, 2009
openaire   +2 more sources

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

Uncertainty quantification in FEM simulation of human liver: sensitivity analysis, Gradient-Enhanced Kriging, and Monte Carlo simulation. [PDF]

Biomech Model Mechanobiol
Waschinsky N, van Meegen C, Lambers L, Ickstadt K, Ricken T.   +4 more
europepmc   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source