Modeling Based on LS-SVM Method and Predicting Dewatering Ratio in Sludge Process

DOI

10.2991/ifeesm-17.2018.22How to use a DOI?

Keywords

Sludge Process; Discharging Sludge; Thickening and Dewatering; Least Square Support Vector Machine; Soft Sensor

Abstract

The sludge produced by treating the urban sewage needs thickening and dewatering and it is important for improving environment to reduce the quantity of discharging sludge by increasing dewatering ratio in sludge process. This paper proposes a novel method that can model least squares support vector machines (LS-SVM) by Soft-sensing to meet the characteristics of multivariable, nonlinearity, large time delay, and time-varying in sludge thickening and dewatering process and predict the dewatering ratio. The results indicate that the proposed method can not only improve prediction accuracy, but also efficiently get high dewatering ratio by controlling thickening chemicals comparing to the cases using different methods.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Fei Luo
AU  - Xinghong Qiao
AU  - Weihao Liao
PY  - 2018/02
DA  - 2018/02
TI  - Modeling Based on LS-SVM Method and Predicting Dewatering Ratio in Sludge Process
BT  - Proceedings of the 2017 3rd International Forum on Energy, Environment Science and Materials (IFEESM 2017)
PB  - Atlantis Press
SP  - 112
EP  - 117
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifeesm-17.2018.22
DO  - 10.2991/ifeesm-17.2018.22
ID  - Luo2018/02
ER  -