Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloGross parameters prediction of a granular-attached biomass reactor by means of multi-objective genetic-designed artificial neural networks: touristic pressure management case
Anno di pubblicazione2015
FormatoElettronico
Autore/iDel Moro G.; Barca E.; de Sanctis M.; Mascolo G.; Di Iaconi C.
Affiliazioni autoriIstituto di Ricerca Sulle Acque, Consiglio Nazionale delle Ricerche, Viale F. De Blasio 5, Bari, 70132, Italy
Autori CNR e affiliazioni
  • CLAUDIO DI IACONI
  • EMANUELE BARCA
  • MARCO DE SANCTIS
  • GUIDO DEL MORO
  • GIUSEPPE MASCOLO
Lingua/e
  • inglese
Abstract[object Object]The Artificial Neural Networks by Multi-objective Genetic Algorithms (ANN-MOGA) model has been applied to gross parameters data of a Sequencing Batch Biofilter Granular Reactor (SBBGR) with the aim of providing an effective tool for predicting the fluctuations coming from touristic pressure. Six independent multivariate models, which were able to predict the dynamics of raw chemical oxygen demand (COD), soluble chemical oxygen demand (CODsol), total suspended solid (TSS), total nitrogen (TN), ammoniacal nitrogen (N-NH4 +) and total phosphorus (Ptot), were developed. The ANN-MOGA software application has shown to be suitable for addressing the SBBGR reactor modelling. The R2 found 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 and TSS, respectively. A comparison was made between SBBGR and traditional activated sludge treatment plant modelling. The results showed the better performance of the ANNMOGA application with respect to a wide selection of scientific literature cases.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da-
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Pagine totali17
RivistaEnvironmental science and pollution research international
Attiva dal 1994
Editore: Springer - Berlin
Paese di pubblicazione: Germania
Lingua: inglese
ISSN: 0944-1344
Titolo chiave: Environmental science and pollution research international
Titolo proprio: Environmental science and pollution research international.
Titolo abbreviato: Environ. sci. pollut. res. int.
Titoli alternativi:
  • Environmental science and pollution research international (Print)
  • Environmental science and pollution research (Print)
  • ESPR (Print)
Numero volume della rivista-
Fascicolo della rivista-
DOI10.1007/s11356-015-5729-3
Verificato da refereeSì: Internazionale
Stato della pubblicazionePreprint
Indicizzazione (in banche dati controllate)
  • Scopus (Codice:2-s2.0-84947087078)
Parole chiaveArtificial neural networks, Fixed-bed bioreactors, Predictive models, Touristic pressure, Wastewater treatment
Link (URL, URI)http://www.scopus.com/inward/record.url?eid=2-s2.0-84947087078&partnerID=q2rCbXpz
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Note/Altre informazioni-
Strutture CNR
  • IRSA — Istituto di ricerca sulle acque
Moduli/Attività/Sottoprogetti CNR-
Progetti Europei-
Allegati
Gross parameters prediction of a granular-attached biomass reactor by means of multi-objective genetic-esigned artificial neural networks (documento privato )
Tipo documento: application/pdf