Results 211 to 220 of about 82,122 (260)

Development and Applications of a Magnetism‐Aware General‐Purpose Atomic Cluster Expansion Potential for the Fe‐O‐H Ternary System

Advanced Science, EarlyView.
Hydrogen‐driven iron oxide reduction, water‐iron corrosion, and hydrogen embrittlement of metallic iron share the same Fe‐O‐H chemistry. A general‐purpose Atomic Cluster Expansion potential covers this chemistry across the full concentration range with explicit Ising‐like treatment of magnetism.
Baptiste Bienvenu, Mira Todorova, Jörg Neugebauer, Dierk Raabe, Matous Mrovec, Ralf Drautz   +5 more
wiley   +1 more source

Editorial: Soft computing and machine learning applications for healthcare systems. [PDF]

Front Artif Intell
Adebiyi AA, Daramola O, Viriri S, Adetiba E.   +3 more
europepmc   +1 more source

Non-invasive prediction of lymph node involvement in prostate cancer via machine learning on whole-prostate MRI. [PDF]

Front Oncol
Luo Y, Liu B, Qin P, Lin Z, Lin T, Wang Y.   +5 more
europepmc   +1 more source

Axial Load Capacity Prediction of Concrete-Filled Steel Tubes Using Machine Learning: A Comparative Study. [PDF]

Materials (Basel)
Chen B, He W, Huang L, Shi X.
europepmc   +1 more source

Prognostic value of heart rate variability for neurological outcomes in cardiac arrest patients: machine learning-based analysis of the International Cardiac Arrest Research (I-CARE) database. [PDF]

Resusc Plus
Liu A, Chen X, Xu X, Li C, Zhou B.
europepmc   +1 more source

Maize yield prediction using machine learning: a systematic literature review. [PDF]

Front Artif Intell
Nyengere J, Tchuwa F, Tholo HM, Malalu L, Njala AL, Kachulu P, Maganga R, Matewere B, Jamu L, Nyirenda C, Kanjira J, Chabwera M, Nalivata P, Mwase W, Mwangwela A.   +14 more
europepmc   +1 more source

Developing and validating machine learning models to predict vaccine hesitancy and literacy among adults in the United States. [PDF]

Front Public Health
Zheng Y, Frew PM, Wang D, Song Y, Patterson-Lomba O, Feizi A, Li T, Eiden AL.   +7 more
europepmc   +1 more source

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Information-Extreme Machine Learning of On-Board Vehicle Recognition System

Cybernetics and Systems Analysis, 2020
The article proposes a categorical model and algorithm for information-extreme machine learning of the on-board recognition system for small ground vehicles. The decision rules constructed as a result of machine learning are invariant to an arbitrary position of the object of recognition in the frame of the region of interest.
A. S. Dovbysh, M. M. Budnyk, V. Yu. Piatachenko, M. I. Myronenko   +3 more
openaire   +1 more source

Solution of Biharmonic Equation in Complicated Geometries With Physics Informed Extreme Learning Machine

Journal of Computing and Information Science in Engineering, 2020
Abstract Recently, physics informed neural networks (PINNs) have produced excellent results in solving a series of linear and nonlinear partial differential equations (PDEs) without using any prior data. However, due to slow training speed, PINNs are not directly competitive with existing numerical methods.
Vikas Dwivedi, Balaji Srinivasan
openaire   +1 more source

Physics-Informed Extreme Learning Machine (PIELM) for Stefan problems

Computer Methods in Applied Mechanics and Engineering
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fei Ren, Pei-Zhi Zhuang, Xiaohui Chen, Hai-Sui Yu, He Yang   +4 more
openaire   +2 more sources