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Developing deep learning surrogate models for digital twins in mineral processing – A case study on data-driven multivariate multistep forecasting
Research article (Minerals Engineering, 2024) · cited 20× · AI/ML
Developing deep learning surrogate models for digital twins in mineral processing – A case study on data-driven multivariate multistep forecasting
Summary
Developing deep learning surrogate models for digital twins in mineral processing – A case study on data-driven multivariate multistep forecasting is a scholarly article[1].
Key Facts
Developing deep learning surrogate models for digital twins in mineral processing – A case study on data-driven multivariate multistep forecasting's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Developing deep learning surrogate models for digital twins in mineral processing – A case study on data-driven multivariate multistep forecasting. Retrieved May 24, 2026, from https://4ort.xyz/entity/developing-deep-learning-surrogate-models-for-digital-twins-in-mineral-processing-a-case-study-on-data-driven-multivaria
MLA“Developing deep learning surrogate models for digital twins in mineral processing – A case study on data-driven multivariate multistep forecasting.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/developing-deep-learning-surrogate-models-for-digital-twins-in-mineral-processing-a-case-study-on-data-driven-multivaria.
BibTeX@misc{4ortxyz_developing-deep-learning-surrogate-models-for-digital-twins-in-mineral-processing-a-case-study-on-data-driven-multivaria_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Developing deep learning surrogate models for digital twins in mineral processing – A case study on data-driven multivariate multistep forecasting}}, year = {2026}, url = {https://4ort.xyz/entity/developing-deep-learning-surrogate-models-for-digital-twins-in-mineral-processing-a-case-study-on-data-driven-multivaria}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Developing deep learning surrogate models for digital twins in mineral processing – A case study on data-driven multivariate multistep forecasting — https://4ort.xyz/entity/developing-deep-learning-surrogate-models-for-digital-twins-in-mineral-processing-a-case-study-on-data-driven-multivaria (retrieved 2026-05-24)
