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Titolo:
Construction of COD simulation model for activated sludge process by fuzzyneural network
Autore:
Tomida, S; Hanai, T; Ueda, N; Honda, H; Kobayashi, T;
Indirizzi:
Nagoya Univ, Grad Sch Engn, Dept Biotechnol, Chikusa Ku, Nagoya, Aichi 4648603, Japan Nagoya Univ Nagoya Aichi Japan 4648603 a Ku, Nagoya, Aichi 4648603, Japan
Titolo Testata:
JOURNAL OF BIOSCIENCE AND BIOENGINEERING
fascicolo: 2, volume: 88, anno: 1999,
pagine: 215 - 220
SICI:
1389-1723(199908)88:2<215:COCSMF>2.0.ZU;2-T
Fonte:
ISI
Lingua:
ENG
Keywords:
activated sludge process; fuzzy neural network; chemical oxygen demand; simulation;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Agriculture,Biology & Environmental Sciences
Life Sciences
Citazioni:
14
Recensione:
Indirizzi per estratti:
Indirizzo: Kobayashi, T Nagoya Univ, Grad Sch Engn, Dept Biotechnol, Chikusa Ku, FuroCho, Nagoya,Aichi 4648603, Japan Nagoya Univ Furo Cho Nagoya Aichi Japan 4648603 648603, Japan
Citazione:
S. Tomida et al., "Construction of COD simulation model for activated sludge process by fuzzyneural network", J BIOSCI BI, 88(2), 1999, pp. 215-220

Abstract

Fuzzy neural network (FNN) was applied to construct a simulation model forestimating the effluent chemical oxygen demand (COD) value of an activatedsludge process in a "U" plant, in which most of process variables were measured once an hour. 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 higher accuracy than the MRA model. The FNN models corresponding to each of the four seasonswere also constructed. Analyzing the fuzzy rules acquired from the FNN models after learning, the operational characteristic of this plant could be elucidated. Construction of the simulation model for another plant "A", in which process variables were measured once a day, was also carried out. ThisFNN model also had a relatively high accuracy.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 26/01/20 alle ore 10:38:46