中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Recurrent high order neural network modeling for wastewater treatment process

文献类型:期刊论文

作者Qiao JF(乔俊飞); Yang WW(杨维维); Yuan MZ(苑明哲)
刊名Journal of Computers
出版日期2011
卷号6期号:8页码:1570-1577
关键词wastewater treatment recurrent high order neural network filtering
ISSN号1796-203X
产权排序2
通讯作者乔俊飞
中文摘要Due to the multi-variable, nonlinear, large time delay and strong coupling features of the wastewater treatment process, a recurrent high-order neural network is used to model the key water quality parameters(Chemical Oxygen Demand, Biological Oxygen Demand, Suspended Solid and Ammonia Nitrogen) for the wastewater treatment process, and the neural network is trained by an filtering algorithm. Operational data of a wastewater treatment plant is employed to illustrate the efficacy of the proposed modeling method. Meanwhile, the results are compared with feed-forward neural network and the general recurrent neural network to indicate the modeling accuracy of the recurrent high-order neural network.
收录类别EI
语种英语
源URL[http://ir.sia.cn/handle/173321/19904]  
专题沈阳自动化研究所_工业信息学研究室
推荐引用方式
GB/T 7714
Qiao JF,Yang WW,Yuan MZ. Recurrent high order neural network modeling for wastewater treatment process[J]. Journal of Computers,2011,6(8):1570-1577.
APA Qiao JF,Yang WW,&Yuan MZ.(2011).Recurrent high order neural network modeling for wastewater treatment process.Journal of Computers,6(8),1570-1577.
MLA Qiao JF,et al."Recurrent high order neural network modeling for wastewater treatment process".Journal of Computers 6.8(2011):1570-1577.

入库方式: OAI收割

来源:沈阳自动化研究所

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