Long-term prediction of industrial furnace by Extended Sequential Prediction method of LOM

Masatoshi Ogawa, Yichun Yeh, Syou Kawanari, Harutoshi Ogai

研究成果: Conference contribution

2 引用 (Scopus)

抜粋

Recently, attention has been drawn by the local modeling techniques of a new idea called "Just-In-Time (JIT) modeling" or "Lazy Learning". To apply "JIT modeling" to a large amount of database online, "Large-scale database-based Online Modeling (LOM)" has been proposed. LOM is such a technique that makes the retrieval of "neighboring" data more efficient by using "stepwise selection" and quantization. This paper reports an Extended Sequential Prediction (ESP) method of LOM with the local regression model. The ESP method is able to predict process variables over a long period by modeling the operator and the plant based on LOM, the approach is to repeat a process that predicts the process variables of the next step by using the predicted variables of the previous step. The method is applied to a dynamic industrial furnace with several deeply-intertwined physical phenomena; practical effectiveness of the method is verified. As a result, the method has predicted the process variables with satisfactory accuracy.

元の言語English
ホスト出版物のタイトルProceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers
出版者Society of Instrument and Control Engineers (SICE)
ページ1490-1493
ページ数4
ISBN(印刷物)9784907764364
出版物ステータスPublished - 2010 1 1

出版物シリーズ

名前Proceedings of the SICE Annual Conference

    フィンガープリント

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

これを引用

Ogawa, M., Yeh, Y., Kawanari, S., & Ogai, H. (2010). Long-term prediction of industrial furnace by Extended Sequential Prediction method of LOM. : Proceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers (pp. 1490-1493). [5602285] (Proceedings of the SICE Annual Conference). Society of Instrument and Control Engineers (SICE).