Application of fuzzy neural network in burden surface clustering

Author

Liu, Dexin ; Li, Xiaoli ; Lu, Shuting ; Ding, Dawei ; Chen, Xianzhong

Author_Institution

Sch. of Autom. & Electr. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China

fYear

2012

fDate

23-25 May 2012

Firstpage

1094

Lastpage

1099

Abstract

Blast furnace charging distribution plays an important role in the steel production. The radar data containing the information of present burden surface situation and the cross thermometer data reflecting the trend of burden surface are taken as the training data of fuzzy neural network. The trained network will be used for the future clustering of the data. Considering the demand of energy-saving and consumption-decreasing, the method sets up the basic for the distribution control in the next step. The simulation results show the effectiveness of the proposed method.

Keywords

blast furnaces; energy conservation; fuzzy neural nets; pattern clustering; power distribution control; radar applications; steel manufacture; thermometers; blast furnace charging distribution; burden surface clustering; burden surface situation; distribution control; energy consumption; energy-saving; fuzzy neural network; radar data; steel production; thermometer data; Blast furnaces; Clustering algorithms; Fuzzy control; Fuzzy neural networks; Radar measurements; Surface treatment; Burden Surface; Cluster; Fuzzy Neural Network;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2012 24th Chinese

Conference_Location

Taiyuan

Print_ISBN

978-1-4577-2073-4

Type

conf

DOI

10.1109/CCDC.2012.6244174

Filename

6244174