A Simulation Model for Activated Sludge Process Using Fuzzy Neural Network View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2000

AUTHORS

Taizo Hanai , Shuta Tomida , Hiroyuki Honda , Takeshi Kobayashi

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. More... »

PAGES

253-258

Book

TITLE

Artificial Neural Networks in Medicine and Biology

ISBN

978-1-85233-289-1
978-1-4471-0513-8

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4471-0513-8_38

DOI

http://dx.doi.org/10.1007/978-1-4471-0513-8_38

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1048374216


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