Results 101 to 110 of about 23,025 (301)
EPJ Web of Conferences, 2017 In the context of the rising of Monte Carlo transport calculations for any kind of application, AREVA recently improved its suite of engineering tools in order to produce efficient Monte Carlo workflow.
Chapoutier Nicolas +4 more
doaj +1 more source
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 +4 more
wiley +1 more source
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 +3 more
wiley +1 more source
Task offloading scheme in Mobile Augmented Reality using hybrid Monte Carlo tree search (HMCTS)
Alexandria Engineering JournalMobile Augmented Reality (MAR) applications enhance user experiences by providing realistic information about the current location through mobile devices.
Anitha Jebamani Soundararaj +1 more
doaj +1 more source
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
Derivative-Variance Hybrid Global Sensitivity Measure with Optimal Sampling Method Selection
MathematicsThis paper proposes a derivative-variance hybrid global sensitivity measure with optimal sampling method selection. The proposed sensitivity measure is as computationally efficient as the derivative-based global sensitivity measure, which also serves as ...
Jiacheng Liu +5 more
doaj +1 more source
An improved hybrid Monte Carlo method
Physics Letters B, 1989 Abstract The hybrid Monte Carlo algorithm does not completely remove problems with ergodicity in the molecular dynamics trajectories unless the length of each trajectory, τ 0 , is kept shorter than the period of the fastest mode of the system, 2 π / ω max .
openaire +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source
Quantum dynamical Hamiltonian Monte Carlo
Physical Review ResearchOne of the open challenges in quantum computing is to find meaningful and practical methods to leverage quantum computation to accelerate classical machine-learning workflows.
Owen Lockwood +3 more
doaj +1 more source