Results 221 to 230 of about 1,407,468 (324)

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, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source

Investigation of inter-source and intra-source spectral variations in an electronic brachytherapy source using spectral measurements and Monte Carlo simulations. [PDF]

Med Phys
Esmaelbeigi A, Tomic N, Kalinowski J, Watson PGF, Rivard MJ, Devic S, Enger SA.   +6 more
europepmc   +1 more source

Latent Causal Flow: Continuous Confounder Disentanglement for Time Series via Monte Carlo Flow Matching

Chen Song
openalex   +1 more source

A New Modification of Ridge Parameter for Regression Problems: A Monte Carlo Simulation Study

, 2019
Arzu Altın Yavuz
openalex   +1 more source

A Data‐Centric Approach to Quantifying the Forward and Inverse Relationship Between Laser Powder Bed Fusion Process Parameters and as‐Built Surface Roughness of IN718 Parts

Advanced Intelligent Systems, EarlyView.
This study introduces the first inverse machine learning model to predict laser powder bed fusion process parameters for targeted surface roughness of Inconel 718 parts. Unlike prior approaches, it incorporates spatial surface characteristics for improved accuracy.
Samsul Mahmood, Bart Raeymaekers
wiley   +1 more source

Health risk assessment of penconazole fungicide residues in grapes: insights from Monte Carlo simulation. [PDF]

Sci Rep
Peirovi-Minaee R, Zarei A, Alami A, Afsharnia M.   +3 more
europepmc   +1 more source

Effect of Current Density on the Dynamical Evolution of Liquid Water Distribution within the Gas Diffusion Layers of PEMFC Employing a Multi-Timescale Kinetic Monte Carlo Method

, 2019
Anahid Pournemat, Florian Wilhelm, Joachim Scholta   +2 more
openalex   +1 more source

Machine Learning‐Based Standard Compact Model Binning Parameter Extraction Methodology for Integrated Circuit Design of Next‐Generation Semiconductor Devices

Advanced Intelligent Systems, EarlyView.
This study presents a neural network‐based methodology for Berkeley Short‐Channel IGFET Model–Common Multi‐Gate parameter extraction of gate‐all‐around field effect transistors, integrating binning adaptive sampling and transformer neural networks to efficiently capture current–voltage and capacitance–voltage characteristics.
Jaeweon Kang, Johyeon Kim, Sueyeon Kim, Hyunbo Cho, Jongwook Jeon   +4 more
wiley   +1 more source

Comparison of two Monte Carlo approaches for homogeneous bulk samples. [PDF]

J Microsc
Gao D, Yuan Y, Brodusch N, Gauvin R.
europepmc   +1 more source

Monte Carlo method for the Spatially Homogenous Boltzmann equation

Abdujabar Rasulov, Gulnora Raimova
openalex   +1 more source