Abstract
In order to construct a simulation model for estimating the effluent chemical oxygen demand (COD) value of an activated sludge process in a “U” plant, fuzzy neural network (FNN) was applied. The constructed FNN model could simulate periodic changes in COD with high accuracy. Comparing the simulation result obtained using the FNN model with that obtained using the multiple regression analysis (MRA) model, it was found that the FNN model had 3.7 times lower error than the MRA model. The FNN models corresponding to each of the four seasons were also constructed. Analyzing the fuzzy rules acquired from the FNN models after learning, the operational characteristic of this plant could be elucidated.
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References
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© 2000 Springer-Verlag London
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Hanai, T., Tomida, S., Honda, H., Kobayashi, T. (2000). A Simulation Model for Activated Sludge Process Using Fuzzy Neural Network. In: Malmgren, H., Borga, M., Niklasson, L. (eds) Artificial Neural Networks in Medicine and Biology. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0513-8_38
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DOI: https://doi.org/10.1007/978-1-4471-0513-8_38
Publisher Name: Springer, London
Print ISBN: 978-1-85233-289-1
Online ISBN: 978-1-4471-0513-8
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