A Comparative Study of the Efficacy of Local/Global and Parametric/Nonparametric Machine Learning Methods for Establishing Structure–Property Linkages in High-Contrast 3D Elastic Composites | Zendy

Patxi Fernandez-Zelaia | Zendy; Yuksel C. Yabansu | Zendy; Surya R. Kalidindi | Zendy

Open Access

A Comparative Study of the Efficacy of Local/Global and Parametric/Nonparametric Machine Learning Methods for Establishing Structure–Property Linkages in High-Contrast 3D Elastic Composites

Author(s) -

Patxi Fernandez-Zelaia,

Yuksel C. Yabansu,

Surya R. Kalidindi

Publication year - 2019

Publication title -

integrating materials and manufacturing innovation

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.878

H-Index - 22

eISSN - 2193-9772

pISSN - 2193-9764

DOI - 10.1007/s40192-019-00129-4

Subject(s) - nonparametric statistics , parametric statistics , curse of dimensionality , contrast (vision) , property (philosophy) , computer science , finite element method , machine learning , gaussian process , artificial intelligence , process (computing) , sensitivity (control systems) , gaussian , data mining , mathematics , engineering , structural engineering , statistics , philosophy , physics , epistemology , quantum mechanics , electronic engineering , operating system

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