Operation space design of microbial fuel cells combined anaerobic-anoxic-oxic process based on support vector regression inverse model
Wang, Jing1; Wang, Qilun1; Zhou, Jinglin1; Wang, Xiaohui2; Cheng, Long3
2018-06-01
发表期刊ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
卷号72页码:340-349
文章类型Article
摘要Microbial Fuel Cells (MFCs) can produce power at the same time of wastewater treatment, which is a new technique for environmental protection and new energy. An appropriate space design of operation variables is very important to improve the performance of MFC process. This paper presents a space design method based on data-driven model but not the traditional mechanism model, which is easy to accomplish in a fast and cost-effective mode. The support vector regression (SVR) forward and inverse model are deduced with the quadratic kernel function, in which the quadratic kernel function is suitable for the mathematical formula in the inversion stage. And the space design of operation variables are proposed to calculate directly from the inverse model with the effect of confidence interval when the model prediction uncertainty are considered. The proposed design method is verified in the real MFC-A(2)/O equipment. It is shown that the designated operation space is a narrow and effective region of the knowledge space which brackets the entire fraction of the MFC experiment space. And in general terms, the possible product quality from the designated operation space is more densely concentrated on the desired value compared to the tradition forward model design method.
关键词Mfc-a(2)/o Operation Space Design Support Vector Regression Inverse Model Prediction Uncertainty Estimation
WOS标题词Science & Technology ; Technology
DOI10.1016/j.engappai.2018.04.005
关键词[WOS]WASTE-WATER TREATMENT ; REMOVAL ; SYSTEM ; PERFORMANCE ; NITROGEN
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(61573050 ; Beijing Natural Science Foundation(4162066) ; open-project grant - State Key Laboratory of Synthetical Automation for Process Industry at the Northeastern University(PAL-N201702) ; 61473025 ; 61633016)
WOS研究方向Automation & Control Systems ; Computer Science ; Engineering
WOS类目Automation & Control Systems ; Computer Science, Artificial Intelligence ; Engineering, Multidisciplinary ; Engineering, Electrical & Electronic
WOS记录号WOS:000434239000028
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/22046
专题复杂系统管理与控制国家重点实验室_先进机器人
作者单位1.Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
2.Beijing Univ Chem Technol, Beijing Engn Res Ctr Environm Mat Water Purificat, Coll Chem Engn, Beijing 100029, Peoples R China
3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
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Wang, Jing,Wang, Qilun,Zhou, Jinglin,et al. Operation space design of microbial fuel cells combined anaerobic-anoxic-oxic process based on support vector regression inverse model[J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,2018,72:340-349.
APA Wang, Jing,Wang, Qilun,Zhou, Jinglin,Wang, Xiaohui,&Cheng, Long.(2018).Operation space design of microbial fuel cells combined anaerobic-anoxic-oxic process based on support vector regression inverse model.ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,72,340-349.
MLA Wang, Jing,et al."Operation space design of microbial fuel cells combined anaerobic-anoxic-oxic process based on support vector regression inverse model".ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 72(2018):340-349.
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