The COD predictive technique based on neural network

Author

Yanliang Ye ; Yan Zhuang

Author_Institution

Dept. of Sci. Res., Beihua Univ., Jilin, China

fYear

2013

fDate

20-22 Dec. 2013

Firstpage

1009

Lastpage

1012

Abstract

A new online COD predictive technique is proposed in this paper for sewage treatment plants. The technique utilizes the BP neural network method and Elman neural network method to build a model and adopts the real operating data of a chemical industry to establish the model for training and simulation. The results of the simulations indicate that the process variables can be achieved through the establishment of the network model and a reasonable choice of the auxiliary input variable in the complex systems of online prediction.

Keywords

backpropagation; neurocontrollers; predictive control; sewage treatment; BP neural network method; Elman neural network method; auxiliary input variable; chemical industry; complex systems; network model; online COD predictive technique; process variables; real operating data; sewage treatment plants; Biological neural networks; Effluents; Prediction algorithms; Sewage treatment; Standards; Training; BP neural network; COD; Elman neural network; auxiliary input variables; sewage treatment;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronic Sciences, Electric Engineering and Computer (MEC), Proceedings 2013 International Conference on

Conference_Location

Shengyang

Print_ISBN

978-1-4799-2564-3

Type

conf

DOI

10.1109/MEC.2013.6885208

Filename

6885208