JOURNAL OF CHEMICAL ENGINEERING OF JAPAN
Online ISSN : 1881-1299
Print ISSN : 0021-9592
Safety, Environment and Energy
Construction of COD Simulation Model for Activated Sludge Process by Recursive Fuzzy Neural Network
SHUTA TOMIDATAIZO HANAIHIROYUKI HONDATAKESHI KOBAYASHI
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2001 Volume 34 Issue 3 Pages 369-375

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Abstract

Using a fuzzy neural network (FNN), we constructed a simulation model which estimates the effluent chemical oxygen demand (COD) value from daily routine measurements. Since the water quality of wastewater is changing day by day, an FNN model with a recursively renewing method of learning data (R-FNN) is proposed. With this R-FNN, learning data used to construct an FNN model are renewed with elapsed time so as to estimate the effluent COD value with good accuracy. The estimation results for 9 weeks data using R-FNN were compared with those using a conventional FNN. The average error using the R-FNN model was 0.36 mg/l, while that using the conventional FNN was 1.50 mg/l. Moreover, estimation of the effluent COD throughout one year was carried out, and the average error was only 0.40 mg/l. This result can show the usefulness of the R-FNN for the simulation model of the activated sludge process.

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© 2001 The Society of Chemical Engineers, Japan
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