Multi-objective optimization and analysis model of sintering process based on BP neural network

被引：38
|
作者：
Zhang Jun-hong [1 ]
Xie An-guo
Shen Feng-man
机构：
[1] Anshan Univ Sci & Technol, Anshan 114044, Liaoning, Peoples R China
[2] Northeastern Univ, Inst Ferrous Met, Shenyang 110004, Peoples R China
来源：
JOURNAL OF IRON AND STEEL RESEARCH INTERNATIONAL | 2007年 / 14卷 / 02期
关键词：
BP neural network; multi-objective; optimization; sinter;
D O I：
10.1016/S1006-706X(07)60018-1
中图分类号：
TF [冶金工业];
学科分类号：
0806 ;
摘要：
A multi-objective optimization and analysis model of the sintering process based on BP neural network is presented. Genetic algorithms are combined to simplify the BP neural network, which can reduce the learning time and increase the forecasting accuracy of the network model. This model has been experimented in the sintering process, and the production cost, the energy consumption, the quality (revolving intensity), and the output are considered at the same time. Moreover, the relation between some factors and the multi-objectives has been analyzed, and the results are consistent with the process. Different objectives are emphasized at different practical periods, and this can provide a theoretical basis for the manager.
引用
收藏
页码：1 / 5
页数：5
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