Particle swarm optimization fuzzy neural network and its application in soft-sensor modeling of acrylonitrile yield

被引：0
|
作者：
Xu, Yu-Fa [1 ,2 ]
Chen, Guo-Chu [1 ]
Yu, Jin-Shou [2 ]
机构：
[1] Shanghai DianJi Univ, Sch Elect Engn, Shanghai 200240, Peoples R China
[2] East China Univ Sci & Technol, Res Inst Automat, Shanghai 200237, Peoples R China
来源：
PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2007年
基金：
上海市自然科学基金;
关键词：
particle swarm optimization algorithm; fuzzy neural networks; acrylonitrile; soft-sensor; modelling;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Firstly, particle swarm optimization fuzzy neural network (PSOFNN) is proposed and the algorithm flow of PSOFNN are given in this paper. Secondly, PSOFNN is applied in soft-sensor modeling of acrylonitrile yield. The new method assumes that fuzzy neural network (FNN) is used to construct the soft-sensor model of acrylonitrile yield and particle swarm optimization algorithm (PSO) is employed to optimize parameters of FNN. Moreover, how to choose the auxiliary variables of soft-sensor is studied carefully. Experiment results show that the model based on PSOFNN has higher precision and better performance than the model based on PSONN. The method proposed by this paper is feasible and effective in soft-sensor of acrylonitrile yield.
引用
收藏
页码：1994 / +
页数：3
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