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1
Ensemble Learning for Predicting the Tensile Strength of Al..:
, In:
2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
,
Kulina, Hristina
;
Koleva-Petrova, Mariana
;
Gocheva-Ilieva, Snezhana
- p. 01-06 , 2022
Link:
https://doi.org/10.1109/ICECCME55909.2022.9988668
RT T1 <cTitle>2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)</cTitle>: T1 <Title>Ensemble Learning for Predicting the Tensile Strength of Alloy Steels from Chemical Composition and Processing Parameters</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9988668&Exemplar=1&LAN=DE A1 Kulina, Hristina A1 Koleva-Petrova, Mariana A1 Gocheva-Ilieva, Snezhana YR 2022 K1 Training K1 Production K1 Predictive models K1 Prediction algorithms K1 Data models K1 Mechanical factors K1 Steel K1 tensile strength K1 low alloy steels K1 ensemble method K1 arcing K1 machine learning SP 01 OP 06 LK http://dx.doi.org/https://doi.org/10.1109/ICECCME55909.2022.9988668 DO https://doi.org/10.1109/ICECCME55909.2022.9988668 SF ELIB - SuUB Bremen
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