Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaos neural network model
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.
Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaos neural network model
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.
Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaos neural network model
Li, Xiaodong (Autor:in) / Zeng, Guangming (Autor:in) / Huang, Guohe (Autor:in) / Li, Jianbing (Autor:in) / Jiang, Ru (Autor:in)
01.07.2007
5 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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