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A novel approach to predict the effect of chemical composition and thermo-mechanical processing parameters on Cu–Ni–Si alloys using a hybrid deep learning and ensemble learning model
Research article (Composites Communications, 2024) · cited 10× · AI/ML
A novel approach to predict the effect of chemical composition and thermo-mechanical processing parameters on Cu–Ni–Si alloys using a hybrid deep learning and ensemble learning model
Summary
A novel approach to predict the effect of chemical composition and thermo-mechanical processing parameters on Cu–Ni–Si alloys using a hybrid deep learning and ensemble learning model is a scholarly article[1].
Key Facts
A novel approach to predict the effect of chemical composition and thermo-mechanical processing parameters on Cu–Ni–Si alloys using a hybrid deep learning and ensemble learning model's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). A novel approach to predict the effect of chemical composition and thermo-mechanical processing parameters on Cu–Ni–Si alloys using a hybrid deep learning and ensemble learning model. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-novel-approach-to-predict-the-effect-of-chemical-composition-and-thermo-mechanical-processing-parameters-on-cunisi-all
MLA“A novel approach to predict the effect of chemical composition and thermo-mechanical processing parameters on Cu–Ni–Si alloys using a hybrid deep learning and ensemble learning model.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-novel-approach-to-predict-the-effect-of-chemical-composition-and-thermo-mechanical-processing-parameters-on-cunisi-all.
BibTeX@misc{4ortxyz_a-novel-approach-to-predict-the-effect-of-chemical-composition-and-thermo-mechanical-processing-parameters-on-cunisi-all_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A novel approach to predict the effect of chemical composition and thermo-mechanical processing parameters on Cu–Ni–Si alloys using a hybrid deep learning and ensemble learning model}}, year = {2026}, url = {https://4ort.xyz/entity/a-novel-approach-to-predict-the-effect-of-chemical-composition-and-thermo-mechanical-processing-parameters-on-cunisi-all}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A novel approach to predict the effect of chemical composition and thermo-mechanical processing parameters on Cu–Ni–Si alloys using a hybrid deep learning and ensemble learning model — https://4ort.xyz/entity/a-novel-approach-to-predict-the-effect-of-chemical-composition-and-thermo-mechanical-processing-parameters-on-cunisi-all (retrieved 2026-05-24)
