Research on prediction method of sludge bulking based on ANN and grey Markov model
文献类型:会议论文
作者 | Yu GP(于广平); Wang JY(王景杨); Yuan MZ(苑明哲); Yu Y(郁洋) |
出版日期 | 2015 |
会议名称 | 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER) |
会议日期 | June 8-12, 2015 |
会议地点 | Shenyang, China |
关键词 | prediction of sludge bulking rough set theory artificial neural networks soft measurement techniques |
页码 | 1622-1627 |
中文摘要 | Sludge volume index (SVI) can evaluate and reflect the aggregation of activated sludge sediment properties accurately. It is an important parameter to predict sludge bulking. Generally, if SVI value is too high, the description is sludge settling performance is poor. It will occur or has occurred sludge bulking. But SVI cannot be online measurement, offline assay data obtained for a long time or other issues. To solve this problem, this paper has applied soft-sensing technology for the sludge volume index that reflects sludge bulking, using rough set to reduce the instrumental variables then construct the soft-sensing model with RBF neural network to complete the dataset of sludge volume index, and then, employed the grey Markov model to predict the dataset to collect the important information of sludge bulking in the quantitative respect, in order to achieve real-time prediction of sludge bulking. |
收录类别 | EI ; CPCI(ISTP) |
产权排序 | 1 |
会议录 | 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER) |
会议录出版者 | IEEE |
会议录出版地 | Piscataway, NJ, USA |
语种 | 英语 |
ISSN号 | 2379-7711 |
ISBN号 | 978-1-4799-8730-6 |
WOS记录号 | WOS:000380502300295 |
源URL | [http://ir.sia.cn/handle/173321/17377] |
专题 | 沈阳自动化研究所_信息服务与智能控制技术研究室 |
推荐引用方式 GB/T 7714 | Yu GP,Wang JY,Yuan MZ,et al. Research on prediction method of sludge bulking based on ANN and grey Markov model[C]. 见:2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER). Shenyang, China. June 8-12, 2015. |
入库方式: OAI收割
来源:沈阳自动化研究所
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