Paper Title:
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.

  Info
Periodical
Chapter
Chapter 5: Model and Optimization and Simulation
Edited by
Zhixiang Hou
Pages
1246-1249
DOI
10.4028/www.scientific.net/AMM.128-129.1246
Citation
N. N. Zhang, K. W. Liu, B. D. Zhang, "The End-Point Ingredient Prediction of Low Carbon Ferrochrome Smelt Based on the Working Condition", Applied Mechanics and Materials, Vols. 128-129, pp. 1246-1249, 2012
Online since
October 2011
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Price
$32.00
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