SIA OpenIR  > 广州中国科学院沈阳自动化研究所分所
Alternative TitleOnline Fault Diagnosis of Wastewater Treatment Process Based on ELM-AdaBoost.M2
谭承诚; 于广平; 邱志成
Source Publication计算机测量与控制
Contribution Rank2
Funding Organization广东省科技项目(2016B090918113)
Keyword污水处理 故障诊断 极限学习机 Adaboost.m2 在线建模
Other AbstractWastewater treatment exists strong nonlinearity, unsteady operation and other characteristics, the online fault diagnosis of wastewater treatment process in reducing pollution and ensure the safety is of great significance. Concerning the low accuracy of fault diagnosis induced by the unbalanced distribution of wastewater treatment process’running state, an online fault diagnosis model based on extreme learning machine (ELM)and AdaBoost.M2 is proposed. Firstly, set ELM as weak classifier and then use AdaBoost.M2 to embody several weak classifiers into strong classifier. The simulation experiments demonstrated that this online diagnosis model has higher precision, faster speed, better generalization ability, and outstanding performance, while comparing to the traditional ones. Therefore, the proposed model can meet the requirements of online fault diagnosis of wastewater treatment process 
Document Type期刊论文
Corresponding Author谭承诚
Recommended Citation
GB/T 7714
谭承诚,于广平,邱志成. 基于ELM-AdaBoost.M2的污水处理过程在线故障诊断[J]. 计算机测量与控制,2018,26(2):53-56.
APA 谭承诚,于广平,&邱志成.(2018).基于ELM-AdaBoost.M2的污水处理过程在线故障诊断.计算机测量与控制,26(2),53-56.
MLA 谭承诚,et al."基于ELM-AdaBoost.M2的污水处理过程在线故障诊断".计算机测量与控制 26.2(2018):53-56.
Files in This Item: Download All
File Name/Size DocType Version Access License
基于ELM_AdaBoost_M2的污水(1404KB)期刊论文作者接受稿开放获取ODC PDDLView Download
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[谭承诚]'s Articles
[于广平]'s Articles
[邱志成]'s Articles
Baidu academic
Similar articles in Baidu academic
[谭承诚]'s Articles
[于广平]'s Articles
[邱志成]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[谭承诚]'s Articles
[于广平]'s Articles
[邱志成]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 基于ELM_AdaBoost_M2的污水处理过程在线故障诊断.pdf
Format: Adobe PDF
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.