Multi-sensor Fusion and Feature Selection in Ultraviolet-Visible Spectrometry System for Predicting Chemical Oxygen Demand

被引：0

作者：

Zhang, Jian ^{[1
]}

Hou, Dibo ^{[1
]}

Huang Ping-jie ^{[1
]}

Zhang, Guangxin ^{[1
]}

Dai, Leilei ^{[1
]}

Li, Jiachen ^{[1
]}

Lu, Tianlong ^{[1
]}

Liu, Shu ^{[1
]}

机构：

[1] Zhejiang Univ, Dept Control Sci & Engn, State Key Lab Ind Control Technol, Hangzhou 310027, Peoples R China

来源：

11TH IEEE INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION (ICCA) | 2014年

关键词：

physic-chemical parameters; feature selecting; chemical oxygen demand; Ultraviolet/Visible spectroscopy; WASTE-WATER;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The ultraviolet-visible (UV-Vis) spectrometry system is increasingly employed in chemical oxygen demand (COD) predicting recently for its significant advantages compared with traditional standard chemical method. In this study, an investigation is undertaken to determine whether the physic-chemical parameters of samples provide a good compensation for prediction. Meanwhile, a feature selecting algorithm is employed to reduce the size of UV-Vis absorption spectroscopy provided as data input to the modeling algorithm. A high correlation of above 0.90 is obtained with the data using the stand chemical method, while less absorbance values are necessary to measure and a spectrometer with industrial wavelength resolution is adequate.

引用

页码：904 / 907

页数：4

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