Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaos neural network model |
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Authors: | Li Xiaodong Zeng Guangming Huang Guohe Li Jianbing Jiang Ru |
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Affiliation: | (1) 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. Translated from Acta Scientiae Circumstantiae, 2006, 26(3): 416–419 [译自: 环境科学学报] |
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Keywords: | wastewater treatment plant (WWTP) influent quantity short-term forecasting time series chaos neural network model |
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