SIA OpenIR  > 广州中国科学院沈阳自动化研究所分所
Alternative TitleEffluent COD Prediction of Urban Sewage Treatment Based on Machine Learning Algorithm
李健1; 刘坚1; 于广平1,2
Conference Name31th Chinese Process Control Conference (CPCC 2020)
Conference DateJuly 30 - August 1, 2020
Conference PlaceXuzhou, China
Source Publication31th Chinese Process Control Conference (CPCC 2020)
Contribution Rank1
Keyword城镇污水 机器学习 支持向量机 COD预测
Other AbstractEffluent COD is the key index to measure the effect of sewage treatment. Due to the large lag of sewage treatment, its detection value has limited effect on the dynamic control of the treatment process. Therefore, it is necessary to establish a fast prediction method of the effluent COD to guide the optimal control of the treatment process. In this paper, through machine learning, support vector machine, k-nearest neighbour, decision tree and other algorithms are used to build regression model, based on the influent COD, pH, ammonia nitrogen and DO value of aeration tank of municipal sewage treatment plant, predict effluent COD of sewage treatment plant. The prediction was carried out in a municipal sewage treatment plant in Guangdong Province, by comparing the prediction results of different algorithms and different parameters of the same algorithm, an effective prediction method of COD in municipal sewage treatment effluent is obtained.
Document Type会议论文
Corresponding Author李健
Recommended Citation
GB/T 7714
李健,刘坚,于广平. 基于机器学习算法的城镇污水处理出水COD预测[C],2020:1.
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