[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/p/ufg/qdsems/08-2011.html
   My bibliography  Save this paper

La predizione di curve di crescita batteriche mediante reti neurali

Author

Listed:
  • Crescenzio Gallo
  • Michelangelo De Bonis
  • Daniele Pepe
Abstract
La microbilogia predittiva (PFM – Predictive Food Microbiology) e' un’area multidisciplinare di ricerca della microbiologia alimentare. Essa implementa elementi fondamentali di matematica, microbiologia, ingegneria e chimica per sviluppare ed applicare modelli matematici e per predire la risposta della crescita di microorganismi con determinate variazioni ambientali. Questo articolo ha un duplice scopo: analizzare i modelli matematici gia' esistenti e affermati nel settore e successivamente proporre una tecnica alternativa basata sulle Reti Neurali Artificiali, descrivendo i risultati derivanti dalla loro applicazione alla predizione di curve di crescita batteriche.

Suggested Citation

  • Crescenzio Gallo & Michelangelo De Bonis & Daniele Pepe, 2011. "La predizione di curve di crescita batteriche mediante reti neurali," Quaderni DSEMS 08-2011, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
  • Handle: RePEc:ufg:qdsems:08-2011
    as

    Download full text from publisher

    File URL: http://www.economia.unifg.it/sites/sd01/files/allegatiparagrafo/24-11-2016/q082011.pdf
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ufg:qdsems:08-2011. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Luca Grilli (email available below). General contact details of provider: https://edirc.repec.org/data/emsfoit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.