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基于模糊神經網絡的煉鋼爐靜態建模

Identification of Steelmaking Furnace Based on FNN

    摘要
  • 摘要: 根據煉鋼轉爐的實際采集數據,利用1種新型模糊神經網絡(FNN),對其進行了靜態建模。從理論上論證了該FNN的推理及非線性逼近能力。用新建模型對鋼水終點溫度,終點含碳量進行計算,其結果與相應的實測值基本一致。

     

    Abstract: The static state model of steelmaking furnace is made based on the reality data gathered with the kind of Fuzzy Neural Network. The objective temperature of steel and WC in steel were calculated by the new model. The results accord with those of measured in the experiment.

     

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