Stabilization temperature prediction in carbon fiber production using empirical mode decomposition and long short-term memory network

Y Guo, S Jiang, J Fu, Y Yang, Y Bao, X Jin - Journal of Cleaner Production, 2023 - Elsevier
Carbon fiber holds significant promise as a sustainable material with diverse applications.
The production of carbon fiber involves a critical process known as oxidative stabilization …

Temperature prediction of submerged arc furnace in ironmaking industry based on residual spatial-temporal convolutional neural network

HX Liu, MJ Li, JQ Guo, XK Zhang, TC Hung - Energy, 2024 - Elsevier
The submerged arc furnace is widely regarded as one of the most promising ore smelting
technologies. However, the real-time monitoring of the multiple physical fields including …

[HTML][HTML] Developing deep learning surrogate models for digital twins in mineral processing–A case study on data-driven multivariate multistep forecasting

A Zeb, J Linnosmaa, M Seppi, O Saarela - Minerals Engineering, 2024 - Elsevier
The escalating demand for environmental and social sustainability underscores the critical
need for large industries such as mining and metallurgy to function optimally. Achieving …

Attention-based deep recurrent neural network to forecast the temperature behavior of an electric arc furnace side-wall

DF Godoy-Rojas, JX Leon-Medina, B Rueda, W Vargas… - Sensors, 2022 - mdpi.com
Structural health monitoring (SHM) in an electric arc furnace is performed in several ways. It
depends on the kind of element or variable to monitor. For instance, the lining of these …

[HTML][HTML] Data-driven classification of the chemical composition of calcine in a ferronickel furnace oven using machine learning techniques

DAV Cardenas, JX Leon-Medina, EJL Pulgarin… - Results in …, 2023 - Elsevier
Calcines' chemical composition analysis is a key process in ferronickel smelting. These
values allow for a clear understanding of the smelted product's expected quality, catering for …

A real-time temperature field prediction method for steel rolling heating furnaces based on graph neural networks

B Yang, L Liu, H Huang, Y Wang, D Li, Q Yang… - International Journal of …, 2024 - Elsevier
In the billet reheating process during steel rolling, the real-time and accurate prediction of
the temperature field is a prerequisite for the dynamic regulation of the heating process …

Data-driven soft sensing towards quality monitoring of industrial pasteurization processes

G Filios, A Kyriakopoulos, S Livanios… - … Computing in Sensor …, 2022 - ieeexplore.ieee.org
In the food and beverage industry many foods, beers and soft drinks usually need to get
pasteurized, a process that holds a significant role in the quality and taste of the final product …

Sensor data prediction in missile flight tests

SG Ryu, JJ Jeong, DH Shim - Sensors, 2022 - mdpi.com
Sensor data from missile flights are highly valuable, as a test requires considerable
resources, but some sensors may be detached or fail to collect data. Remotely acquired …

[图书][B] Neural Computing for Advanced Applications: Third International Conference, NCAA 2022, Jinan, China, July 8–10, 2022, Proceedings, Part I

H Zhang, Y Chen, X Chu, Z Zhang, T Hao, Z Wu… - 2022 - books.google.com
The two-volume Proceedings set CCIS 1637 and 1638 constitutes the refereed proceedings
of the Third International Conference on Neural Computing for Advanced Applications …

A Machine Learning Rapid Prediction of the Aerothermodynamic Environment for Near-Space Hypersonic Unmanned Aircraft

X Chen, W Fan - Tsinghua Science and Technology, 2024 - ieeexplore.ieee.org
Near-space hypersonic unmanned aircrafts (NHUA) encounter significant aerodynamic
heating effects when flying at high velocities in extreme conditions. This leads to the …