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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

Application of an artificial neural network (ANN) simulator to increase the operational efficiency of a roadheader. [PDF]

Sci Rep
Cheluszka P, Głuszek G, Rostami J.
europepmc   +1 more source

The repaired man or the man with extras: medical human-cyborgs. [PDF]

Front Digit Health
Speer G.
europepmc   +1 more source

Artificial intelligence in gastrointestinal and hepatopancreatobiliary surgery: innovations, integration, and future directions. [PDF]

Ann Med Surg (Lond)
Dholakia VA, Jena SS, Nundy S.
europepmc   +1 more source

Dynamic multi objective task scheduling in cloud computing using reinforcement learning for energy and cost optimization. [PDF]

Sci Rep
Yu X, Mi J, Tang L, Long L, Qin X.
europepmc   +1 more source

Evaluating actual use of outdoor exercise equipment in a community park in Southern California through video-captured behavioral assessment. [PDF]

Discov Public Health
Sami M, Macridis S, Ogunseitan OA.
europepmc   +1 more source

A scalable scheduling and resource management framework for cloud-native B2B applications. [PDF]

Sci Rep
Komarasamy D, Rajavel R, Harimoorthy K, Pitchai A.   +3 more
europepmc   +1 more source