Nonylphenol biodegradation kinetics estimation using neural networks

Rubeena Shaik, Raúl Ordóñez, Ravi Ramachandran

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Many man made chemical substances are coming under the focus for environmental abuse and their impact on wild life and humans. A widely used alkylphenolethoxylates (APEs) surfactant was recently banned in Europe because scientists discovered that APE breakdown products are estrogenic and highly toxic to aquatic organisms . Nonylphenol is one such substance that has come under the focus as an environmental pollutant. However, sufficient information is not there to study the kinetic behavior of this toxic surfactant. The biodegradation process of nonylphenol is best described by Monod's model which is based on a coupled system of nonlinear differential equations. This model is based on set of kinetic parameters. It is very difficult to measure the actual biodegradation process of nonylphenol because of the unknown nature of the parameters involved and expense in measuring the states. The estimation of kinetic parameters of nonylphenol biodegradation is done by using a gradient optimization neural network estimator.

    Original languageEnglish (US)
    Title of host publicationISCAS 2006
    Subtitle of host publication2006 IEEE International Symposium on Circuits and Systems, Proceedings
    Pages4224-4227
    Number of pages4
    StatePublished - Dec 1 2006
    EventISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems - Kos, Greece
    Duration: May 21 2006May 24 2006

    Publication series

    NameProceedings - IEEE International Symposium on Circuits and Systems
    ISSN (Print)0271-4310

    Other

    OtherISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems
    Country/TerritoryGreece
    CityKos
    Period5/21/065/24/06

    All Science Journal Classification (ASJC) codes

    • Electrical and Electronic Engineering

    Fingerprint

    Dive into the research topics of 'Nonylphenol biodegradation kinetics estimation using neural networks'. Together they form a unique fingerprint.

    Cite this