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COREX冷煤氣成分預測的二步建模方法

Two-stage modeling method for predicting COREX cold gas content

  • 摘要: 針對熔融氣化爐冷煤氣成分含量,提出了基于熵權模糊C均值聚類和偏最小二乘的COREX冷煤氣成分預測方法.建模過程中首先根據料單中各種原料的單耗量,利用熵權模糊C均值聚類的方法將料單聚類成若干種料單類別,然后針對不同的料單類別,利用偏最小二乘法分別建立冷煤氣成分預測模型.對寶鋼COREX-1#爐實際生產數據驗證結果表明:該方法可以有效地建立COREX冷煤氣成分預測模型,具有較好的預測精度.

     

    Abstract: A method for predicting cold gas content in a melter-gasifier was proposed based on entropy-weighted fuzzy C-means clustering and partial least squares(PLS).In the modeling process,an entropy-weighted fuzzy C-means clustering algorithm is used to get the clustering result of burden calculation reports according to the consumption of raw materials at first.Then,different prediction models are built based on a PLS algorithm for various cluster types.The real field data of cold gas content from Baosteel COREX-1# were used for verification.It is shown that the method can build the prediction model of COREX cold gas content effectively,and has an advantage in prediction accuracy.

     

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