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Prediction of blast furnace operation using on-line bayesian learning

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6 Author(s)
Kaneko, N. ; Dept. of Electr. Eng. & Biosci., Waseda Univ., Tokyo ; Sakamoto, S. ; Uchida, K. ; Ogai, H.
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The large scale database-based online modeling, called LOM, is a type of just-in-time modeling for blast furnace. In this paper, we propose a new type of LOM using a nonlinear local model to improve the performance of the long-term prediction. To estimate the parameter of the nonlinear local model, we use on-line Bayesian learning scheme with sequential Monte Carlo. The prediction performance of the new LOM is demonstrated by using the real process data of blast furnace.

Published in:

Control, Automation and Systems, 2008. ICCAS 2008. International Conference on

Date of Conference:

14-17 Oct. 2008