Biochemical Oxygen Demand Soft Measurement Based On LE-RVM

DOI

10.2991/icsd-16.2017.35How to use a DOI?

Keywords

Wastewater treatment; BOD; Nonlinear dimension reduction; RVM

Abstract

In order to solve the modeling problem of biochemical oxygen demand (BOD) in wastewater treatment process. This paper proposes an online BOD predictive method based on Laplacian Eigenmaps - Relevance Vector Machine ( LE-RVM) . First, the easy to obtain the parameters of the wastewater treatment process is acquired, and then the data preprocessing. The preprocessed parameters is processed by LE, and then is applied as input of RVM to build the soft measurement model of BOD. Experiments show that the prediction model is effective with higher convergence speed. The prediction model indicated that the new methods has better recognition effect and higher computation speed.

Copyright

© 2017, 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  - Long Luo
PY  - 2016/12
DA  - 2016/12
TI  - Biochemical Oxygen Demand Soft Measurement Based On LE-RVM
BT  - Proceedings of the 2nd 2016 International Conference on Sustainable Development (ICSD 2016)
PB  - Atlantis Press
SP  - 164
EP  - 167
SN  - 2352-5401
UR  - https://doi.org/10.2991/icsd-16.2017.35
DO  - 10.2991/icsd-16.2017.35
ID  - Luo2016/12
ER  -