Performance Forecast of IF Steel Mass-Produced in Bao Steel

CHU Yuanzhang; QI Peng; ZHANG Ya

doi:10.13374/j.issn1001-053x.2001.01.040

Volume 23 Issue 1

Aug. 2021

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CHU Yuanzhang, QI Peng, ZHANG Ya. Performance Forecast of IF Steel Mass-Produced in Bao Steel[J]. Chinese Journal of Engineering, 2001, 23(1): 48-51. doi: 10.13374/j.issn1001-053x.2001.01.040

Citation:

CHU Yuanzhang, QI Peng, ZHANG Ya. Performance Forecast of IF Steel Mass-Produced in Bao Steel[J]. Chinese Journal of Engineering, 2001, 23(1): 48-51. doi: 10.13374/j.issn1001-053x.2001.01.040

CHU Yuanzhang, QI Peng, ZHANG Ya. Performance Forecast of IF Steel Mass-Produced in Bao Steel[J]. Chinese Journal of Engineering, 2001, 23(1): 48-51. doi: 10.13374/j.issn1001-053x.2001.01.040

Citation:

CHU Yuanzhang, QI Peng, ZHANG Ya. Performance Forecast of IF Steel Mass-Produced in Bao Steel[J]. Chinese Journal of Engineering, 2001, 23(1): 48-51. doi: 10.13374/j.issn1001-053x.2001.01.040

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Performance Forecast of IF Steel Mass-Produced in Bao Steel

doi: 10.13374/j.issn1001-053x.2001.01.040

Material Science and Engineering School, UST Beijing, Beijing 100083, China

Received Date: 2000-07-04

Abstract

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