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Author Naranjo, F.C. ♦ Leiva, G.A.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2010
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Training ♦ Biological system modeling ♦ Computational modeling ♦ Artificial neural networks ♦ neural networks ♦ Data models ♦ time-varying parameters ♦ Mathematical model ♦ Equations ♦ chemical processes ♦ gray-box neural model
Abstract Gray-box neural models mix differential equations, which act as white boxes, and neural networks, used as black boxes, to complete the phenomenological model. These models have been used in different researches proving their efficacy. The aim of this work is to show the training of the gray-box model through indirect back propagation and Levenberg-Marquardt. The gray-box neural model was tested in the simulation of a chemical process in a continuous stirred tank reactor (CSTR) with 5% noise, responding successfully.
ISBN 9781457700736
ISSN 15224902
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2010-11-15
Publisher Place Chile
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 410.89 kB
Page Count 5
Starting Page 265
Ending Page 269


Source: IEEE Xplore Digital Library