Electrode regulating system modeling in electrical smelting furnace using recurrent neural network with attention mechanism-Reference-Cited by-同舟云学术

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Electrode regulating system modeling in electrical smelting furnace using recurrent neural network with attention mechanism

Published:2019-09 Issue: Volume:359 Page:32-40
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Ding Shenyi,Wang Zhijie,Kong Weijian,Yang Honghai,Song Guangxiao^ORCID

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference34 articles.

1. Data-driven demand forecasting method for fused magnesium furnaces;Yang,2016

2. Very short-term demand forecasting for fused magnesium furnaces based on specific penalty function;Yang,2014

3. Intelligent control of fused magnesium furnaces based on SPSA;Wu;J. Shanghai Jiaotong Univ.,2011

4. Hybrid intelligent optimal control of fused magnesium furnaces;Wu,2010

5. Intelligent Control Algorithm of Electric-Fused Magnesia Furnace Based on Neural Network;Ma,2014

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1. Prediction of abnormal conditions for fused magnesium furnace based on improved LSTM model and rule-based reasoning;Measurement;2023-08

2. Dynamic convolutional gated recurrent unit attention auto-encoder for feature learning and fault detection in dynamic industrial processes;International Journal of Production Research;2022-12-14

3. Feature Sequencing Method of Industrial Control Data Set Based on Multidimensional Evaluation Parameters;Computational Intelligence and Neuroscience;2022-04-28

4. Modeling of dynamic data-driven approach for the distributed steel rolling heating furnace temperature field;Neural Computing and Applications;2022-02-18

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