Hybrid Modeling of Molten Steel Temperature Prediction in LF

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概要

• 論文の詳細を見る

• Combining the conventional mechanism method with the newly developed intelligent algorithm, a hybrid model was developed for predicting the molten steel temperature in LF. The mechanism method is used to build the thermal model by analyzing the energy going into and out of the molten steel during the LF refining production process. It is hard to calculate the coefficients in the thermal model by mechanism method, so they are estimated by experience traditionally. In this paper, a new ensemble ELM algorithm using the modified AdaBoost.RT is proposed to calculate these coefficients. The new hybrid model overcomes the difficulty of obtaining the coefficients in thermal model, and solves the problem of limited prediction precision using “black box” model. The experiment demonstrates that the new hybrid model can improve generalization performance and the prediction accuracy.

• 社団法人 日本鉄鋼協会の論文
• 2008-01-15

著者

• Wang Yan

  Information Science And Engineering College

• Tian Huixin

  School Of Electrical And Automation Engineering Tianjin Polytechnic Univ.

• Mao Zhizhong

  Key Lab. Of Integrated Automation Of Process Ind. Northeastern Univ.

• TIAN Huixin

  Information Science and Engineering College

• MAO Zhizhong

  Information Science and Engineering College

関連論文

• A Novel Fault Diagnosis System for Blast Furnace Based on Support Vector Machine Ensemble
• Hybrid Modeling of Molten Steel Temperature Prediction in LF
• A New Incremental Learning Modeling Method Based on Multiple Models for Temperature Prediction of Molten Steel in LF

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