ELM based LF temperature prediction model and its online sequential learning

Proceedings of the 2012 24th Chinese Control and Decision Conference, CCDC 2012

Volumn , Issue , 2012, Pages 2362-2365

  Lv, Wu ^a   Mao, Zhizhong ^a,b   Jia, Mingxing ^a  

^a NORTHEASTERN UNIVERSITY   (China)

^b STATE KEY LABORATORY OF SYNTHETICAL AUTOMATION FOR PROCESS INDUSTRIES   (China)

Author keywords

ELM; LF temperature prediction model; online sequential learning; SLFNs

Indexed keywords

ACCURATE PREDICTION; ELM; EXTREME LEARNING MACHINE; FAST LEARNING; FORGETTING FACTORS; GENERALIZATION PERFORMANCE; LADLE FURNACES; LEARNING SCHEMES; MOLTEN STEEL; OPTIMAL CONTROLS; PREDICTION MODEL; PRODUCTION PROCESS; SEQUENTIAL LEARNING; SINGLE-HIDDEN LAYER FEEDFORWARD NEURAL NETWORKS; SLFNS; TEMPERATURE PREDICTION;

FEEDFORWARD NEURAL NETWORKS; LEARNING ALGORITHMS; MATHEMATICAL MODELS; STEEL FOUNDRY PRACTICE;

E-LEARNING;

EID: 84866691640     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CCDC.2012.6244378     Document Type: Conference Paper

References (8)

1. U. Camdali and M. Tumc, Energy and Exergy analysis of a Ladle Furnace, Canadian Metallurgical Quarterly, 42(4): 439-446, 2003.
2. U. Camdali and M. Tumc, Steady State Heat Transfer of Ladle Furnace During Steel Production Process, Journal of Iron and Steel Research, 13(3): 18-20, 2006.
3. G.B. Huang, Q.Y. Zhu, and C.K. Siew, Extreme learning machine: Theory and applications, Neurocomputing, 70(1): 489-501, 2006.
4. G.B. Huang, Q.Y. Zhu, and C.K. Siew, Extreme learning machine: A new learning scheme of feedforward neural networks, in Proceedings of IEEE International Joint Coference on Neural Networks, 2004:985-990.
5. H.X. Tian, Z.Z. Mao, S. Wang, K. Li, Application of Genetic Algorithm Combined with BP Neural Network in Soft Sensor of Molten Steel Temperature. in Proceedings of the 6th World Congress on Intelligent Control and Automation. 2006:7742-7745.
6. X.L. Wang, The Research of LF Liquid Steel Temperature Prediction Based on PLS-SVM Algorithm, in Automation Research and Design Institute of Metallurgical Industr., Beijing, 2007.
7. N.Y. Liang, G.B. Huang, A Fast and Accurate Online Sequential Learning Algorithm for Feedforward Networks. IEEE Transactions on Neural Networks, 17(6):1411-1423, 2006.
8. G.H. Golub and C.F.V. Loan, matrix computations, 3rd Edition. The Johns Hopkins University Press, Baltimore, 1996.