Prediction of Endpoint Phosphorus Content of Molten Steel in BOF Using Weighted K-Means and GMDH Neural Network

Author:

Wang Hong-bing,Xu An-jun,Ai Li-xiang,Tian Nai-yuan

Publisher

Springer Science and Business Media LLC

Subject

Materials Chemistry,Metals and Alloys,Mechanics of Materials

Reference20 articles.

1. Narra R, Malaya R K, Shyamal K P. Feed Forward Neural Network for Prediction of End Blow Oxygen in LD Converter Steel Making [J]. Materials Research, 2010, 13(1): 15.

2. Frattini Fileti A M, Pacianotto T A, Pitasse Cunha A. Neural Modeling Helps the BOS Process to Achieve Aimed End-Point Conditions in Liquid Steel [J]. Engineering Applications of Artificial Intelligence, 2006, 19(1): 9.

3. Anupam Das, Maiti J, Banerjee R N. Process Control Strategies for a Steel Making Furnace Using ANN With Bayesian Regularization and ANFIS [J]. Experts Systems With Applications, 2010, 37(2): 1075.

4. LI Chang-rang, ZHAO Hao-wen, XIE Xiang, et al. Prediction of End-Point Phosphorus Content for BOF Based on LM BP Neural Network [J]. Iron and Steel, 2011, 46(4): 23 (in Chinese).

5. YANG Li-hong, LIU Liu, HE Ping. Prediction and Control Model of End Phosphorus Content for Oxygen-Converter Based on Adaptive Neutro-Fussy System [J]. Journal of Iron and Steel Research, 2002, 14(4): 47 (in Chinese).

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