| 基于机器学习算法的印染废水出水COD预测 | |
| Alternative Title | Effluent 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
 |
| ISSN | 1007-1865 |
| 2020 | |
| Volume | 47Issue:10Pages:83-84 |
| Contribution Rank | 1 |
| 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 |
| Identifier | http://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 |
| Affiliation | 1.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. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| 基于机器学习算法的印染废水出水COD预测（1090KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
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