宝钢IF钢大生产产品性能预测

基金项目:

国家"九五"攻关资助项目（No.9527-01-01-09）

详细信息

Performance Forecast of IF Steel Mass-Produced in Bao Steel

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.
- BP算法 /
- IF钢 /
- 性能预测
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 σ_b,δ₁, r and n are all less than 5.0% except that on σ_0.2 is 9.0%. It is concluded that this system has a higher forecast precision than the multivariant linear regression model.
- BP algorithm /
- IF steel /
- performance forecast