Research on Intellectual Prediction for Permeability Index of Blast Furnace

被引：3

作者：

Liang Dong ^{[1
,2
]}

Bai Chen-guang ^{[2
]}

Shi Hong-yan ^{[1
]}

Dong Jie-ji ^{[1
]}

机构：

[1] Shandong Laiwu Steel Grp Ltd, Ctr Res & Dev, Tsinan 271104, Shandong, Peoples R China

[2] Chongqing Univ, Coll Mat Sci & Engn, Chongqing 400044, Peoples R China

来源：

PROCEEDINGS OF THE 2009 WRI GLOBAL CONGRESS ON INTELLIGENT SYSTEMS, VOL I | 2009年

关键词：

Blast furnace; Permeability Index; Wavelet decomposition; SVM; DISCRIMINANT-ANALYSIS;

D O I：

10.1109/GCIS.2009.427

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Permeability index of BF is an important monitoring parameter in operation Proper trend prediction of the permeability index is vital for a good operator Support Vector Machines combined with the Wavelet Analysis is adopted to build the forecasting model. Four historic values of permeability index are decomposed by Wavelet via seven levels, based on eight Wavelet decomposition combined with operational parameters, using Least Square Support Vector Machines method (LS-SVM), eight sub-models are bud. Predicting component are reconstructed to gain the forecast The detail of modeling, validation and results analysis are presented.

引用

页码：299 / +

页数：2

共 6 条

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