Modeling of Fermentation Process Based on QDPSO-SVM

被引：2
|
作者：
Wang, Xianfang [1 ]
Chen, Jindong [1 ]
Wu, Zhou [1 ]
Pan, Feng [1 ]
机构：
[1] Jiangnan Univ, Sch Commun & Control Engn, Jiangsu 214122, Peoples R China
来源：
ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 7, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/ICNC.2008.176
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Utilizing the ability simple in application and quick in convergence of Quantum Delta-potential-well-based Particle Swarm Optimization (QDPSO) algorithm and the high generalization ability of Support Vector Machine (SVM), selecting the appropriate state variables, a dynamic time-varying model has been built. Using the model and algorithm to per-estimate some biochemical state variables which can not be measured on-lineand to optimize some operational variables. It is proved that the method is efficiency through the practical application of penicillin fermentation process.
引用
收藏
页码：186 / 190
页数：5
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