| 宝钢IF钢大生产产品性能预测 |
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| 引用本文： | 初元璋,祁鹏,张娅.宝钢IF钢大生产产品性能预测[J].北京科技大学学报,2001,23(1):48-51. |
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| 作者姓名： | 初元璋 祁鹏 张娅 |
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| 作者单位： | 北京科技大学材料科学与工程学院, |
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| 基金项目： | 国家科技攻关项目;95-527-01-01-09; |
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| 摘 要： | 以ＢＰ算法为基础开发了ＡＮＮ学习预测系统，用于宝钢ＩＦ钢大生产产品性能预测．同时，应用在宝钢ＩＦ钢大生产数据对该系统进行了测试和分析，并与多元线性回归结果进行预测精度比较．结果表明，ＡＮＮ学习预测系统，除σ_(０.２)误差较高（９．０％）外，σ_ｂ，δ，ｒ和ｎ值均＜５．０％，且比多线性回归方法精度高．
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| 关 键 词： | BP算法 IF钢 ANN学习预测系统 宝钢 化学成分 温度参数 产品性能预测 多元线性回归 |
| 修稿时间： | 2000年7月4日 |
Performance Forecast of IF Steel Mass-Produced in Bao Steel |
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| CHUN Yuanzhang,Qi Peng,ZHANG Ya.Performance Forecast of IF Steel Mass-Produced in Bao Steel[J].Journal of University of Science and Technology Beijing,2001,23(1):48-51. |
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| Authors: | CHUN Yuanzhang Qi Peng ZHANG Ya |
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| 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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| Keywords: | BP algorithm IF steel performance forecast |
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