Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaos neural network model

doi:10.1007/s11783-007-0057-6

Front.Environ.Sci.Eng.

2007, Vol. 1

Issue (3) : 334-338 https://doi.org/10.1007/s11783-007-0057-6

Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaos neural network model

LI Xiaodong, ZENG Guangming, HUANG Guohe, LI Jianbing, JIANG Ru

College of Environmental Science and Engineering, Hunan University, Changsha 410082, China;

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Abstract By predicting influent quantity, a wastewater treatment plant (WWTP) can be well controlled. The nonlinear dynamic characteristic of WWTP influent quantity time series was analyzed, with the assumption that the series was predictable. Based on this, a short-term forecasting chaos neural network model of WWTP influent quantity was built by phase space reconstruction. Reasonable forecasting results were achieved using this method.

Issue Date: 05 September 2007

Cite this article:

ZENG Guangming,LI Xiaodong,HUANG Guohe, et al. Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaos neural network model[J]. Front.Environ.Sci.Eng., 2007, 1(3): 334-338.

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https://academic.hep.com.cn/fese/EN/10.1007/s11783-007-0057-6
https://academic.hep.com.cn/fese/EN/Y2007/V1/I3/334

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