Predicting Steel Grade Based on Electric Arc Furnace End Point Parameters
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-56826-8_20
Reference11 articles.
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2. Stavropoulos, P., Panagiotopoulou, V.C., Papacharalampopoulos, A., Aivaliotis, P., Georgopoulos, D., Smyrniotakis, K.: A framework for CO2 emission reduction in manufacturing industries: a steel industry case. Designs 6(2), 22 (2022). https://doi.org/10.3390/designs6020022
3. Feng, K., Wang, H., Xu, A., He, D.: Endpoint temperature prediction of molten steel in RH using improved case-based reasoning. Int. J. Miner. Metall. Mater. 20(12), 1148–1154 (2013). https://doi.org/10.1007/s12613-013-0848-7
4. Jo, H., Hwang, H.J., Phan, D., Lee, Y., Jang, H.: Endpoint temperature prediction model for LD converters using machine-learning techniques. In: 2019 IEEE 6th International Conference on Industrial Engineering and Applications (ICIEA), pp. 22–26 (2019). https://doi.org/10.1109/IEA.2019.8715073
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