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

2007, Volume 1, Issue 3

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Frontiers of Environmental Science & Engineering >> 2007, Volume 1, Issue 3 doi: 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

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

Available online: 2007-09-05

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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.

Keywords

nonlinear ; reconstruction ; WWTP influent ; characteristic ; Reasonable forecasting

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