Abstract

The Artificial Neural Networks by Multi-objectiveGenetic Algorithms (ANN-MOGA) model has been appliedto gross parameters data of a Sequencing Batch BiofilterGranular Reactor (SBBGR) with the aim of providing an effectivetool for predicting the fluctuations coming from touristicpressure. Six independent multivariate models, whichwere able to predict the dynamics of raw chemical oxygendemand (COD), soluble chemical oxygen demand (CODsol),total suspended solid (TSS), total nitrogen (TN), ammoniacalnitrogen (N-NH4+) and total phosphorus (Ptot), were developed.The ANN-MOGA software application has shown to besuitable for addressing the SBBGR reactor modelling. The R2found are very good, with values equal to 0.94, 0.92, 0.88,0.88, 0.98 and 0.91 for COD, CODsol, N-NH4+, TN, Ptot andTSS, respectively. A comparison was made between SBBGRand traditional activated sludge treatment plant modelling.The results showed the better performance of the ANNMOGAapplication with respect to a wide selection of scientificliterature cases.

Autore Pugliese

• Di Iaconi Claudio , Barca Emanuele , Mascolo Giuseppe , De Sanctis Marco

Tutti gli autori

• Del Moro G.; Barca E.; de Sanctis M.; Mascolo G.; Di Iaconi C.

Titolo volume/Rivista

Environmental science and pollution research international

Anno di pubblicazione

2015

ISSN

0944-1344

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

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Numero di citazioni Scopus

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Ultimo Aggiornamento Citazioni

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Settori ERC

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Codici ASJC

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