EventsMOL2NET'23, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 9th ed.
Event submissions
Published
This submission belongs to the session 02. CHEMBIO.MOL-09: Org. Chem., Med. Chem., Mol. Biol., & Pharm. Industry Congress, Paris, France-Fargo, USA, 2023. of the event MOL2NET'23, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 9th ed.
Published date
23 Dec, 2023
Academic Editor
author-avatarHumbert G. Díaz
Citation
Karel Diéguez Santana, Galo Cerda-Mejía, Juan M. Ruso, Innovation in Materials: Key Steps for Algorithm Selection in Predicting Mechanical Characteristics through Machine Learning, in Proceedings of MOL2NET'23, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 9th ed., 25 December–31 December 2023, MDPI: Basel, Switzerland
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Innovation in Materials: Key Steps for Algorithm Selection in Predicting Mechanical Characteristics through Machine Learning

image
Galo Cerda-Mejía 1,2
Karel Diéguez Santana 3
Juan M. Ruso 2
1. Universidad Regional Amazónica Ikiam, Parroquia Muyuna km 7 vía Alto Tena, 150150, Tena-Napo, Ecuador
2. Soft Matter and Molecular Biophysics Group, Department of Applied Physics, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain
3. Universidad Regional Amazónica IKIAM
Abstract
Keywords
Algorithm Selection
Data Collection
Data Representation
Materials science
Model Optimization
Manuscript
Manuscript.pdf