Predicting Dynamic Behavior of a Biological System Using ANNs
In: AIP Conference Proceedings, 2008
Online
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Zugriff:
In this paper, artificial neural networks (ANNs) are applied to predict protein concentrations of a biological system. The input data are generated from a nonlinear mathematical model of the protein concentration. The protein concentrations from CDC6 data with actual kinetic parameter are taken as the target output. The data are then trained using multilayer perceptron (MLP) neural network with a 6‐6‐6 configuration. The allocation of the data will be distributed into 3 categories that are 80% as training data, 10% as validation data, and 10% as test data. The learning rules used in this work to determine the best model are gradient descent, conjugate gradient, scaled conjugate gradient. It is found that the MLP with scaled conjugate gradient learning rule gives the best prediction rate.
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Predicting Dynamic Behavior of a Biological System Using ANNs
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Autor/in / Beteiligte Person: | Mohd Haniff Osman ; Ibrahim, Ratnawati ; Hashim, Ishak ; Liong Choong Yeun ; Azuraliza Abu Bakar ; Zeti Azura Mohamed Hussein ; Kamel Ariffin Mohd Atan ; Krishnarajah, Isthrinayagy S. |
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Zeitschrift: | AIP Conference Proceedings, 2008 |
Veröffentlichung: | AIP, 2008 |
Medientyp: | unknown |
ISSN: | 0094-243X (print) |
DOI: | 10.1063/1.2883866 |
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