The End-Point Ingredient Prediction of Low Carbon Ferrochrome Smelt Based on the Working Condition

Niao Na Zhang; Ke Wei Liu; Bao Dong Zhang

doi:10.4028/www.scientific.net/AMM.128-129.1246

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 128-129The End-Point Ingredient Prediction of Low Carbon...

The End-Point Ingredient Prediction of Low Carbon Ferrochrome Smelt Based on the Working Condition

Abstract:

Construct the model of the end-point ingredient prediction of low carbon ferrochrome smelt based on the working condition of electrothermal silicon method using the method of multi-scale support vector machiness information fusion, where the best decomposition scale information is according to different smelt working conditions using Levenberg-Marquart algorithm to optimize the design, smelt working condition is judged by Bayesian classifier. Researches have proved that this method can improve the precision of prediction and make the prediction result more accurate, reasonable and practical.

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Periodical:

Applied Mechanics and Materials (Volumes 128-129)

Pages:

1246-1249

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.128-129.1246

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Online since:

October 2011

Authors:

Niao Na Zhang, Ke Wei Liu, Bao Dong Zhang

Keywords:

Bayesian, End-Point Ingredient, Information Fusion, Low Carbon Ferrochrome

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