Research on RBF Neural Network in Simulation of MBR Membrane Pollution Simulation

被引：0
|
作者：
Chen, Xiangning [1 ]
Li, Chunqing [1 ]
Hu, Wenbo [1 ]
Tang, Jia [1 ]
机构：
[1] Tianjin Polytech Univ, Coll Comp Sci & Software, 399 Bin Shui Xi Rd, Tianjin 300387, Peoples R China
来源：
2017 16TH IEEE/ACIS INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCE (ICIS 2017) | 2017年
基金：
中国国家自然科学基金;
关键词：
MBR; Membrane flux; RBF neural network; BP neural network;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Membrane pollution is the main obstacle to the popularization and application of MBR. In order to solve the problem that the influence factors of membrane fouling are more complicated, three kinds of membrane fouling factors with the contribution rate of more than 95% are selected by principal component analysis(PCA) method: The mixed solution suspended solids (MLSS), operating pressure (P) and temperature (T). The three influencing factors of MBR membrane were simulated and the membrane flux was used as output parameter. The predictive model of membrane fouling based on RBF neural network was established to realize the predictive control of membrane fouling. The whole experimental process has certain theoretical value and practical significance, and it should play an active role in guiding the actual project of MBR.
引用
收藏
页码：387 / 390
页数：4
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