Particle swarm optimization neural network and its application in soft-sensing modeling

被引：0
|
作者：
Chen, GC [1 ]
Yu, JS [1 ]
机构：
[1] E China Univ Sci & Technol, Res Inst Automat, Shanghai 200237, Peoples R China
来源：
ADVANCES IN NATURAL COMPUTATION, PT 2, PROCEEDINGS | 2005年 / 3611卷
关键词：
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：
Particle swarm optimization algorithm (PSO) is applied to train artificial neural network (NN) to construct a neural network based on particle swarm optimitization algorithm (PSONN). Then, PSONN is employed to construct a practical soft-sensor of gasoline endpoint of main fractionator of fluid catalytic cracking unit (FCCU). The obtained results indicate that soft-sensing model based on PSONN has better performance than soft-sensing model based on BPNN and the new method proposed by this paper is feasible and effective in soft-sensing modeling of gasoline endpoint.
引用
收藏
页码：610 / 617
页数：8
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