A sludge volume index (SVI) model based on the multivariate local quadratic polynomial regression method

doi:10.1016/j.cjche.2017.08.007

Chinese Journal of Chemical Engineering ›› 2018, Vol. 26 ›› Issue (5): 1071-1077.DOI: 10.1016/j.cjche.2017.08.007

• Process Systems Engineering and Process Safety • 上一篇下一篇

A sludge volume index (SVI) model based on the multivariate local quadratic polynomial regression method

Honggui Han^1,2, Xiaolong Wu^1,2, Luming Ge^1,2, Junfei Qiao^1,2

1 College of Automation, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China;
2 Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing 100124, China

收稿日期:2017-05-24 修回日期:2017-08-09 出版日期:2018-05-28 发布日期:2018-06-29
通讯作者: Honggui Han,E-mail address:rechardhan@sina.com

A sludge volume index (SVI) model based on the multivariate local quadratic polynomial regression method

Honggui Han^1,2, Xiaolong Wu^1,2, Luming Ge^1,2, Junfei Qiao^1,2

1 College of Automation, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China;
2 Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing 100124, China

Received:2017-05-24 Revised:2017-08-09 Online:2018-05-28 Published:2018-06-29
Contact: Honggui Han,E-mail address:rechardhan@sina.com

摘要/Abstract

摘要： In this study, a multivariate local quadratic polynomial regression (MLQPR) method is proposed to design a model for the sludge volume index (SVI). In MLQPR, a quadratic polynomial regression function is established to describe the relationship between SVI and the relative variables, and the important terms of the quadratic polynomial regression function are determined by the significant test of the corresponding coefficients. Moreover, a local estimation method is introduced to adjust the weights of the quadratic polynomial regression function to improve the model accuracy. Finally, the proposed method is applied to predict the SVI values in a real wastewater treatment process (WWTP). The experimental results demonstrate that the proposed MLQPR method has faster testing speed and more accurate results than some existing methods.

关键词: Sludge volume index, Multivariate quadratic polynomial regression, Local estimation method, Wastewater treatment process

Abstract: In this study, a multivariate local quadratic polynomial regression (MLQPR) method is proposed to design a model for the sludge volume index (SVI). In MLQPR, a quadratic polynomial regression function is established to describe the relationship between SVI and the relative variables, and the important terms of the quadratic polynomial regression function are determined by the significant test of the corresponding coefficients. Moreover, a local estimation method is introduced to adjust the weights of the quadratic polynomial regression function to improve the model accuracy. Finally, the proposed method is applied to predict the SVI values in a real wastewater treatment process (WWTP). The experimental results demonstrate that the proposed MLQPR method has faster testing speed and more accurate results than some existing methods.

Key words: Sludge volume index, Multivariate quadratic polynomial regression, Local estimation method, Wastewater treatment process

Honggui Han, Xiaolong Wu, Luming Ge, Junfei Qiao. A sludge volume index (SVI) model based on the multivariate local quadratic polynomial regression method[J]. Chinese Journal of Chemical Engineering, 2018, 26(5): 1071-1077.

Honggui Han, Xiaolong Wu, Luming Ge, Junfei Qiao. A sludge volume index (SVI) model based on the multivariate local quadratic polynomial regression method[J]. Chin.J.Chem.Eng., 2018, 26(5): 1071-1077.

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A sludge volume index (SVI) model based on the multivariate local quadratic polynomial regression method

A sludge volume index (SVI) model based on the multivariate local quadratic polynomial regression method

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