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Data · dataset · 2019

Data for: Machine learning for hierarchical prediction of elastic properties in Fe-Cr-Al system

Listed in Teesside University Research Data Repository

This data repository provides the raw and standardized data for machine learning presented in the article entitled "Machine learning for hierarchical prediction of elastic properties in Fe-Cr-Al system" by the same authors.

Description

The data are generated by the cluster expansion method. The binary data, which are separated as the training set and test set, are used to construct the extremely randomized trees and deep neural networks models.

And the ternary data of different temperatures are used for predictions.

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Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
Teesside University Research Data Repositoryoai:data.mendeley.com/82b9cczbm2.215 h agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].local:field:computer-science-aimapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
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