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基于机器学习算法的印染废水出水COD预测
Alternative TitleEffluent COD Prediction of Printing and Dyeing Wastewater Based on Machine Learning Algorithm
刘坚1; 李健1; 于广平1,2
Department广州中国科学院沈阳自动化研究所分所
Source Publication广东化工
ISSN1007-1865
2020
Volume47Issue:10Pages:83-84
Contribution Rank1
Funding Organization国家自然科学基金重点项目(61533002) ; 国家自然科学基金重大项目(61890935)
Keyword印染废水 机器学习 COD预测
Abstract

印染废水具有成分复杂、水量大、处理大滞后等特点。化学需氧量(COD)是衡量污水处理效果的核心指标,本文采用了最小二乘法、支持向量机等机器学习算法建立模型对印染废水处理出水COD进行预测,平均误差为1.9mg/L,提供了一种有效预测出水COD的方法,为印染废水处理优化运行提供支撑。

Other Abstract

Printing and dyeing wastewater has the characteristics of complex composition, large amount of water and large lag in treatment. Chemical oxygen demand (COD) is the core index to measure the effect of sewage treatment, in this paper, the least square method, support vector machine and other machine learning algorithms are used to establish a model to predict the effluent COD, the average error is 1.9 mg/L, it provides an effective method to predict the effluent COD for the optimal operation of printing and dyeing wastewater treatment.

Language中文
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/26851
Collection广州中国科学院沈阳自动化研究所分所
Corresponding Author刘坚
Affiliation1.广州中国科学院沈阳自动化研究所分所
2.中国科学院沈阳自动化研究所
Recommended Citation
GB/T 7714
刘坚,李健,于广平. 基于机器学习算法的印染废水出水COD预测[J]. 广东化工,2020,47(10):83-84.
APA 刘坚,李健,&于广平.(2020).基于机器学习算法的印染废水出水COD预测.广东化工,47(10),83-84.
MLA 刘坚,et al."基于机器学习算法的印染废水出水COD预测".广东化工 47.10(2020):83-84.
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