TCN-LSTM: A Deep Learning-Based Temperature Prediction Model for Rotary Kilns
Author:
Affiliation:
1. School of Future Technology, South China University of Technology,Guangzhou,China
2. Pengcheng Laboratory,Shenzhen,China
Funder
National Natural Science Foundation of China
China Postdoctoral Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10450150/10449968/10451546.pdf?arnumber=10451546
Reference26 articles.
1. Hybrid model of a cement rotary kiln using an improved attention-based recurrent neural network
2. Rotary kiln process: An overview of physical mechanisms, models and applications;Huchet;Applied Thermal Engineering,2022
3. Dynamic modelling of a rotary kiln for calcination of titanium dioxide white pigment
4. Temperature prediction for roller kiln based on hybrid first-principle model and data-driven MW-DLWKPCR model
5. Application of the dynamic model of Saeman to an industrial rotary kiln incinerator: Numerical and experimental results
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