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寶鋼IF鋼大生產產品性能預測

Performance Forecast of IF Steel Mass-Produced in Bao Steel

  • 摘要: 以BP算法為基礎開發了ANN學習預測系統,用于寶鋼IF鋼大生產產品性能預測.同時,應用在寶鋼IF鋼大生產數據對該系統進行了測試和分析,并與多元線性回歸結果進行預測精度比較.結果表明,ANN學習預測系統,除σ0.2誤差較高(9.0%)外,σb,δ,rn值均<5.0%,且比多線性回歸方法精度高.

     

    Abstract: Develop ANN learn-forecast system by employing BP algorithm to forecast the performance of IF steel, test and analyze the system by using data collected from BAO Steel, and compare the precision of forecasted data with that of the multivariant linear regression model. The results show that the relative errors of ANN learn-forecast system on σb,δ1, r and n are all less than 5.0% except that on σ0.2 is 9.0%. It is concluded that this system has a higher forecast precision than the multivariant linear regression model.

     

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