کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
581529 | 877844 | 2009 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
On-line estimation of key process variables based on kernel partial least squares in an industrial cokes wastewater treatment plant
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
بهداشت و امنیت شیمی
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![عکس صفحه اول مقاله: On-line estimation of key process variables based on kernel partial least squares in an industrial cokes wastewater treatment plant On-line estimation of key process variables based on kernel partial least squares in an industrial cokes wastewater treatment plant](/preview/png/581529.png)
چکیده انگلیسی
A kernel-based algorithm is potentially very efficient for predicting key quality variables of nonlinear chemical and biological processes by mapping an original input space into a high-dimensional feature space. Nonlinear data structure in the original space is most likely to be linear at the high-dimensional feature space. In this work, kernel partial least squares (PLS) was applied to predict inferentially key process variables in an industrial cokes wastewater treatment plant. The primary motive was to give operators and process engineers a reliable and accurate estimation of key process variables such as chemical oxygen demand, total nitrogen, and cyanides concentrations in real time. This would allow them to arrive at the optimum operational strategy in an early stage and minimize damage to the operating units as shock loadings of toxic compounds in the influent often cause process instability. The proposed kernel-based algorithm could effectively capture the nonlinear relationship in the process variables and show far better performance in prediction of the quality variables compared to the conventional linear PLS and other nonlinear PLS method.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Hazardous Materials - Volume 161, Issue 1, 15 January 2009, Pages 538-544
Journal: Journal of Hazardous Materials - Volume 161, Issue 1, 15 January 2009, Pages 538-544
نویسندگان
Seung Han Woo, Che Ok Jeon, Yeoung-Sang Yun, Hyeoksun Choi, Chang-Soo Lee, Dae Sung Lee,