期刊文献+

Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model 被引量:3

Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model
下载PDF
导出
摘要 A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability. A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7. 1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.
出处 《Journal of Central South University of Technology》 EI 2006年第5期552-557,共6页 中南工业大学学报(英文版)
基金 Project(2002CB312203) supported by the National Key Fundamental Research and Development Programof China pro-ject(60574030) supported bythe National Natural Science Foundation of China project(06FD026) supported bythe Natural Science Foun-dation of Hunan Province , China
关键词 Pb-Zn合金 烧结 控制系统 定量合成模型 多目标优化 智能调整 Pb-Zn sintering blending process qualitative and quantitative synthetic model multi-objectiveoptimization area optimization intelligent coordination
  • 相关文献

参考文献7

二级参考文献29

  • 1涂亚庆,李祖枢.一种新型的仿人智能控制器的设计方法[J].自动化学报,1994,20(5):616-621. 被引量:39
  • 2何磊,戴冠中.分级递阶专家智能控制及其在加氢裂化生产反应过程中的应用[J].信息与控制,1995,24(6):338-342. 被引量:7
  • 3费敏锐,陈伯时,郎文鹏.智能控制方法的交叉综合及其应用[J].控制理论与应用,1996,13(3):273-281. 被引量:32
  • 4傅菊英 姜涛.烧结球团学[M].长沙:中南工业大学出版社,1992..
  • 5肖劲松 王沫然.Matlab5.x与科学计算[M].北京:清华大学出版社,2001..
  • 6王莜留.钢铁冶金学(炼铁部分)[M].北京冶金工业出版社,1995..
  • 7柏林霖.高炉配矿及炉料结构优化研究[J].钢铁,1999,34:195-199.
  • 8范晓慧 李桃 等.人工智能技术在烧结过程控制中的应用[J].矿冶工程,1998,18(9):67-70.
  • 9王亦文 桂卫华 等.基于专家规则模糊分类的烧结透气性分布式神经网络模型[J].中南工业大学学报,2000,10(31):843-846.
  • 10[2]GOMM J B, YU D L. Selecting radial basis function network centers with recursive orthogonal least squares training [J]. IEEE Trans on Neural Networks, 2000, 11(2): 306-314.

共引文献95

同被引文献38

引证文献3

二级引证文献12

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部