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

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摘要 By predicting influent quantity,a wastewater treatment plant(WWTP)can be well controlled.The non-linear 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.
出处 《Frontiers of Environmental Science & Engineering》 SCIE EI CSCD 2007年第3期334-338,共5页 环境科学与工程前沿(英文)
基金 The work was supported by the Natural Science Foundation of China for Distinguished Young Scholars(Grant Nos.50225926 and 50425927) the National High-Tech Research and Development(863)Program of China(Grant No.2004AA649370) the Teaching and Research Award Program for Excellent Youth Teachers in Higher Education Institu-tions of MOE,China(TRAPOYT)in 2000 the Specialized Research Fund for the Doctoral Program of Higher Education of Ministry of Education of China(Grant No.20020532017).
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