Single Spectrum End Point Predict of BOF with SVM
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32771
Single Spectrum End Point Predict of BOF with SVM

Authors: Ling-fei Xu, Qi Zhao, Yan-ru Chen, Mu-chun Zhou, Meng Zhang, Shi-xue Xu

Abstract:

SVM ( Support Vector Machine ) is a new method in the artificial neural network ( ANN ). In the steel making, how to use computer to predict the end point of BOF accuracy is a great problem. A lot of method and theory have been claimed, but most of the results is not satisfied. Now the hot topic in the BOF end point predicting is to use optical way the predict the end point in the BOF. And we found that there exist some regular in the characteristic curve of the flame from the mouse of pudding. And we can use SVM to predict end point of the BOF, just single spectrum intensity should be required as the input parameter. Moreover, its compatibility for the input space is better than the BP network.

Keywords: SVM, predict, BOF, single spectrum intensity.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1075792

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1291

References:


[1] Feng Jie, Zhang Hongwen, BOF steelmaking(M). Beijing: Metallurgical Industry Press, 2006. 332-338.
[2] Sharan A., Light sensors for BOF carbon control in low cabon heats(C). Steelmaking Conference Proceedings, 1998, 81: 337-345.
[3] Hong-yuan Wen, Qi Zhao, Yan-ru Chen, Mu-chun Zhou, Meng Zhang, Ling-fei Xu., IBasic-Oxygen-Furnane Endpoint Forecating Model Based on Radiation and Modified Neural Network(J). ACTA Opitca sinica. 2008, 28(11): 2131-2135.
[4] Hong-yuan Wen, Qi Zhao, Yan-ru Chen, Mu-chun Zhou, Meng Zhang, Ling-fei Xu., TConerter End-point Prediction Model Using Spectum Image Analysis and Improved Neural Network Algorithm(J). Optica Applicata, 2008, 38(4): 693-704.
[5] C. Cortes, V.Vapnik. Support vecter networks(J). Machine Learning, 1995(20): 273-297.
[6] Nello Cristianini, John Shawe-Taylor, An Introduction to Support Vector Machines(M), London: Cambridge University Press, 2006: 54-59.
[7] Wang Weiwei. Time Series Prediction Based on SVM and GA(J). The Eighth International Conference on Electronic Measurement and Instruments,2007,2:307-310.
[8] Weiping Wang, Chengxian Guan, Zhongqing Chen. HF-NQO-100 model oxygen concentration cell(J). Proc. SPIE 4077, 304-308 (2000).