Article references

Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

Dynamic modelling of the electric arc furnace process using artificial neural networks

J.-C. Baumert, R. Engel, C. Weiler

Rev. Met. Paris, 99 10 (2002) 839-849

Published online: 2002-11-12

DOI: https://doi.org/10.1051/metal:2002144

PDF (316.9 KB)

This article has been cited by the following article(s):

I Nyoman Aditya, Lesnanto Multa Putranto, Roni Irnawan and Rian Fatah Mochamad
246 (2024)
https://doi.org/10.1109/ICITEE62483.2024.10808221

Alberto N. Conejo
105 (2024)
https://doi.org/10.1007/978-981-97-4053-6_3

Wenjing Wang, Na Wang, Biao Wang and Zhizhong Mao
6478 (2021)
https://doi.org/10.1109/CCDC52312.2021.9601862

Prediction of Arc Voltage of Electric Arc Furnace Based on Improved Back Propagation Neural Network

K. U. Vinayaka and P. S. Puttaswamy
SN Computer Science 2 (3) (2021)
https://doi.org/10.1007/s42979-021-00556-1

Application and Evaluation of Mathematical Models for Prediction of the Electric Energy Demand Using Plant Data of Five Industrial-Size EAFs

Alexander Reimann, Thomas Hay, Thomas Echterhof, Marcus Kirschen and Herbert Pfeifer
Metals 11 (9) 1348 (2021)
https://doi.org/10.3390/met11091348

Evaluating of the exergy efficiency of the silicon production process using artificial neural networks

Zhengjie Chen, Shichao Zhou, Kuixian Wei, Wenhui Ma and Shaoyuan Li
Phosphorus, Sulfur, and Silicon and the Related Elements 195 (9) 756 (2020)
https://doi.org/10.1080/10426507.2020.1756806

Using Statistical Modeling to Predict the Electrical Energy Consumption of an Electric Arc Furnace Producing Stainless Steel

Leo S. Carlsson, Peter B. Samuelsson and Pär G. Jönsson
Metals 10 (1) 36 (2019)
https://doi.org/10.3390/met10010036

Predicting the Electrical Energy Consumption of Electric Arc Furnaces Using Statistical Modeling

Leo S. Carlsson, Peter B. Samuelsson and Pär G. Jönsson
Metals 9 (9) 959 (2019)
https://doi.org/10.3390/met9090959

Predicting the Electricity Consumption and the Exergetic Efficiency of a Submerged Arc Furnace with Raw Materials using an Artificial Neural Network

Zhengjie Chen, Wenhui Ma, Jijun Wu, et al.
Silicon 10 (2) 603 (2018)
https://doi.org/10.1007/s12633-016-9499-4

Electric Arc Furnace Modeling with Artificial Neural Networks and Arc Length with Variable Voltage Gradient

Raul Garcia-Segura, Javier Vázquez Castillo, Fernando Martell-Chavez, Omar Longoria-Gandara and Jaime Ortegón Aguilar
Energies 10 (9) 1424 (2017)
https://doi.org/10.3390/en10091424

Artifical Intelligence and Soft Computing

Marcin Blachnik, Krystian Mączka and Tadeusz Wieczorek
Lecture Notes in Computer Science, Artifical Intelligence and Soft Computing 6114 371 (2010)
https://doi.org/10.1007/978-3-642-13232-2_45

Predicting the performance of submerged arc furnace with varied raw material combinations using artificial neural network

Veerendra Singh, Vilas Tathavadkar, S. Mohan Rao and K.S. Raju
Journal of Materials Processing Technology 183 (1) 111 (2007)
https://doi.org/10.1016/j.jmatprotec.2006.10.004