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Titolo:
Determination of operating conditions in activated sludge process using fuzzy neural network and genetic algorithm
Autore:
Yoshikawa, H; Hanai, T; Tomida, S; Honda, H; Kobayashi, T;
Indirizzi:
Nagoya Univ, Grad Sch Engn, Dept Biotechnol, Nagoya, Aichi 4648603, Japan Nagoya Univ Nagoya Aichi Japan 4648603 hnol, Nagoya, Aichi 4648603, Japan
Titolo Testata:
JOURNAL OF CHEMICAL ENGINEERING OF JAPAN
fascicolo: 8, volume: 34, anno: 2001,
pagine: 1033 - 1039
SICI:
0021-9592(200108)34:8<1033:DOOCIA>2.0.ZU;2-E
Fonte:
ISI
Lingua:
ENG
Keywords:
activated sludge; fuzzy neural network; simulation; genetic algorithm; reliability index;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
20
Recensione:
Indirizzi per estratti:
Indirizzo: Hanai, T Nagoya Univ, Grad Sch Engn, Dept Biotechnol, Nagoya, Aichi 4648603, Japan Nagoya Univ Nagoya Aichi Japan 4648603 oya, Aichi 4648603, Japan
Citazione:
H. Yoshikawa et al., "Determination of operating conditions in activated sludge process using fuzzy neural network and genetic algorithm", J CHEM EN J, 34(8), 2001, pp. 1033-1039

Abstract

In order to realize control of activated sludge process, a simulation model for effluent chemical oxygen demand (COD) was constructed using the time series data of three months. Here, the recursive fuzzy neural network (RFNN) was applied for the simulation. The simulation model could estimate effluent COD value with relatively high accuracy (average error: 0.68 mg/l). Next, to control effluent COD value to the desirable level, the search system for the values of the control variables, dissolved oxygen concentration (DO) and mixed liquor suspended solid (MLSS), was constructed using the genetic algorithm (GA) and GA with the reliability index (R1), called as RIGA. Insearch for DO and MLSS values, accuracy of GA search system was high (average error: 0.16 mg/l for DO and 214 mg/l for MLSS) and accuracy of RIGA search system was higher than GA (average error: 0.11 mg/l for DO and 144 mg/lfor MLSS). Then, the search using RIGA was further extended for one-year data to check the ability of this system. As a result, the constructed system could search DO and MLSS values with the average errors of 0.10 mg/l and 162 mg/l, respectively.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 06/04/20 alle ore 21:52:41