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Particle swarm optimization method in initialization of wavelet neural network model for fed-batch bioprocesses

Wavelet neural network is an alternative to artificial neural network in empirical modeling of industrial processes due to efficient initialization of network parameters that reduces training time. In this paper, particle swarm optimization methods are used for initialization of dilation and transla...

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Main Authors: Mamat, Nor Hana, Mohd Noor, Samsul Bahari, Che Soh, Azura, Taip, Farah Saleena, Ab Rashid, Ahmad Hazri, Jufika Ahmad, Nur Liyana, Mohd Yusuff, Ishak
Format: Conference or Workshop Item
Language:English
Published: IEEE 2018
Online Access:http://psasir.upm.edu.my/id/eprint/68438/1/Particle%20swarm%20optimization%20method%20in%20initialization%20of%20wavelet%20neural%20network%20model%20for%20fed-batch%20bioprocesses.pdf
http://psasir.upm.edu.my/id/eprint/68438/
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spelling my.upm.eprints.684382019-06-10T02:18:36Z http://psasir.upm.edu.my/id/eprint/68438/ Particle swarm optimization method in initialization of wavelet neural network model for fed-batch bioprocesses Mamat, Nor Hana Mohd Noor, Samsul Bahari Che Soh, Azura Taip, Farah Saleena Ab Rashid, Ahmad Hazri Jufika Ahmad, Nur Liyana Mohd Yusuff, Ishak Wavelet neural network is an alternative to artificial neural network in empirical modeling of industrial processes due to efficient initialization of network parameters that reduces training time. In this paper, particle swarm optimization methods are used for initialization of dilation and translational parameters in two wavelet neural network models. Dissolved oxygen models are constructed from real bioprocess data of pilot scale fed-batch bioreactor in polyhydroxyalkanotes (PHA) production and an industrial-scale fed-batch bioreactor in penicillin production. Simulation output of dissolved oxygen and initial mean square error (IMSE) show that the distance and error between initialization and training data are small in PSO method compared to random and heuristic methods. This ensures training phase start very close to target data. IEEE 2018 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/68438/1/Particle%20swarm%20optimization%20method%20in%20initialization%20of%20wavelet%20neural%20network%20model%20for%20fed-batch%20bioprocesses.pdf Mamat, Nor Hana and Mohd Noor, Samsul Bahari and Che Soh, Azura and Taip, Farah Saleena and Ab Rashid, Ahmad Hazri and Jufika Ahmad, Nur Liyana and Mohd Yusuff, Ishak (2018) Particle swarm optimization method in initialization of wavelet neural network model for fed-batch bioprocesses. In: 2018 8th IEEE International Conference on Control System, Computing and Engineering (ICCSCE 2018), 23-25 Nov. 2018, Penang, Malaysia. (pp. 190-194). 10.1109/ICCSCE.2018.8685024
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Wavelet neural network is an alternative to artificial neural network in empirical modeling of industrial processes due to efficient initialization of network parameters that reduces training time. In this paper, particle swarm optimization methods are used for initialization of dilation and translational parameters in two wavelet neural network models. Dissolved oxygen models are constructed from real bioprocess data of pilot scale fed-batch bioreactor in polyhydroxyalkanotes (PHA) production and an industrial-scale fed-batch bioreactor in penicillin production. Simulation output of dissolved oxygen and initial mean square error (IMSE) show that the distance and error between initialization and training data are small in PSO method compared to random and heuristic methods. This ensures training phase start very close to target data.
format Conference or Workshop Item
author Mamat, Nor Hana
Mohd Noor, Samsul Bahari
Che Soh, Azura
Taip, Farah Saleena
Ab Rashid, Ahmad Hazri
Jufika Ahmad, Nur Liyana
Mohd Yusuff, Ishak
spellingShingle Mamat, Nor Hana
Mohd Noor, Samsul Bahari
Che Soh, Azura
Taip, Farah Saleena
Ab Rashid, Ahmad Hazri
Jufika Ahmad, Nur Liyana
Mohd Yusuff, Ishak
Particle swarm optimization method in initialization of wavelet neural network model for fed-batch bioprocesses
author_facet Mamat, Nor Hana
Mohd Noor, Samsul Bahari
Che Soh, Azura
Taip, Farah Saleena
Ab Rashid, Ahmad Hazri
Jufika Ahmad, Nur Liyana
Mohd Yusuff, Ishak
author_sort Mamat, Nor Hana
title Particle swarm optimization method in initialization of wavelet neural network model for fed-batch bioprocesses
title_short Particle swarm optimization method in initialization of wavelet neural network model for fed-batch bioprocesses
title_full Particle swarm optimization method in initialization of wavelet neural network model for fed-batch bioprocesses
title_fullStr Particle swarm optimization method in initialization of wavelet neural network model for fed-batch bioprocesses
title_full_unstemmed Particle swarm optimization method in initialization of wavelet neural network model for fed-batch bioprocesses
title_sort particle swarm optimization method in initialization of wavelet neural network model for fed-batch bioprocesses
publisher IEEE
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/68438/1/Particle%20swarm%20optimization%20method%20in%20initialization%20of%20wavelet%20neural%20network%20model%20for%20fed-batch%20bioprocesses.pdf
http://psasir.upm.edu.my/id/eprint/68438/
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score 13.211869

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