Modeling energy demand—a systematic literature review
PA Verwiebe, S Seim, S Burges, L Schulz… - Energies, 2021 - mdpi.com
In this article, a systematic literature review of 419 articles on energy demand modeling,
published between 2015 and 2020, is presented. This provides researchers with an …
published between 2015 and 2020, is presented. This provides researchers with an …
Machine learning analysis of electric arc furnace process for the evaluation of energy efficiency parameters
The electric arc furnace has been the subject of extensive research due to its complex and
chaotic nature. Machine learning methods provide a powerful forensic examination of …
chaotic nature. Machine learning methods provide a powerful forensic examination of …
Enhanced prediction of end-point carbon content in electric arc furnaces using Bayesian optimised fully connected neural networks with early stopping
H Zhu, H Lu, Z Jiang, H Li, C Yang, Z Ni… - Ironmaking & …, 2024 - journals.sagepub.com
This study developed a Bayesian optimisation-enhanced fully connected neural network
(BO-EFCNN) model with an early stopping mechanism to predict the end-point carbon …
(BO-EFCNN) model with an early stopping mechanism to predict the end-point carbon …
Decreasing the environmental impact of the electric steel making process through implementation of furnace retrofitting solutions
F Kaiser, T Reichel, T Echterhof, D Mier… - IOP Conference …, 2024 - iopscience.iop.org
Steel production in the electric arc furnace is an energy-intensive process and generates a
high amount of climate-relevant CO 2 emissions. During the last decades, various …
high amount of climate-relevant CO 2 emissions. During the last decades, various …
Tackling Uncertainty: Forecasting the Energy Consumption and Demand of an Electric Arc Furnace with Limited Knowledge on Process Parameters
V Zawodnik, FC Schwaiger, C Sorger, T Kienberger - Energies, 2024 - mdpi.com
The iron and steel industry significantly contributes to global energy use and greenhouse
gas emissions. The rising deployment of volatile renewables and the resultant need for …
gas emissions. The rising deployment of volatile renewables and the resultant need for …
A Proposed Methodology to Evaluate Machine Learning Models at Near-Upper-Bound Predictive Performance—Some Practical Cases from the Steel Industry
LS Carlsson, PB Samuelsson - Processes, 2023 - mdpi.com
The present work aims to answer three essential research questions (RQs) that have
previously not been explicitly dealt with in the field of applied machine learning (ML) in steel …
previously not been explicitly dealt with in the field of applied machine learning (ML) in steel …
Modeling of a continuous charging electric arc furnace metallic loss based on the charge mix
D Mombelli, G Dall'Osto, C Mapelli… - steel research …, 2021 - Wiley Online Library
In the recent years, a revolution of the worldwide development policies has taken place,
mainly driven by the idea of achieving the sustainable development scenario (SDS). The …
mainly driven by the idea of achieving the sustainable development scenario (SDS). The …
A data-driven model for energy consumption analysis along with sustainable production: A case study in the steel industry
M Chavosh Nejad, E Hadavandi… - Energy Sources, Part …, 2022 - Taylor & Francis
Sustainable production is of the most serious concerns that affect production systems. In a
manufacturing company, efficient energy consumption, which leads to significant …
manufacturing company, efficient energy consumption, which leads to significant …
The energy consumption optimization using machine learning technique in electrical arc furnaces (EAF)
The stainless-steel industry is one of the largest growing industries today because of the non-
corrosive property of the alloy and corporate dependence on it. Stainless-steel industries …
corrosive property of the alloy and corporate dependence on it. Stainless-steel industries …
Circular transformation of the European steel industry renders scrap metal a strategic resource
P Klimek, M Hess, M Gerschberger… - arXiv preprint arXiv …, 2024 - arxiv.org
The steel industry is a major contributor to CO2 emissions, accounting for 7% of global
emissions. The European steel industry is seeking to reduce its emissions by increasing the …
emissions. The European steel industry is seeking to reduce its emissions by increasing the …