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

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

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