Cover Image

Comparison of particle swarm optimization and response surface methodology in fermentation media optimization of flexirubin production

At present, response surface methodology (RSM) is the most preferred method for fermentation media optimization. However, in the last two decades, artificial intelligence algorithm has become one of the most efficient methods for empirical modelling and optimization. One of the popular developed app...

Full description

Saved in:
Bibliographic Details
Main Authors: Suhaimi, Siti Nurulasilah, Shamsuddin, Siti Mariyam, Ahmad, Wan Azlina, Hasan, Shafaatunnur, Venil, Chidambaram Kulandaisamy
Format: Article
Language:English
Published: Penerbit UTM Press 2018
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/84731/1/SitiMariyamShamsuddin2019_ComparisonofParticleSwarmOptimizationandResponse.pdf
http://eprints.utm.my/id/eprint/84731/
https://dx.doi.org/10.11113/jt.v81.10766
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.84731
record_format eprints
spelling my.utm.847312020-02-29T12:29:11Z http://eprints.utm.my/id/eprint/84731/ Comparison of particle swarm optimization and response surface methodology in fermentation media optimization of flexirubin production Suhaimi, Siti Nurulasilah Shamsuddin, Siti Mariyam Ahmad, Wan Azlina Hasan, Shafaatunnur Venil, Chidambaram Kulandaisamy QA75 Electronic computers. Computer science At present, response surface methodology (RSM) is the most preferred method for fermentation media optimization. However, in the last two decades, artificial intelligence algorithm has become one of the most efficient methods for empirical modelling and optimization. One of the popular developed approaches is Particle Swarm Optimization (PSO), which is used in optimizing a problem. This paper focuses on comparative studies between RSM and PSO in fermentation media optimization for the production of flexirubin production using Chryseobacterium artocarpi CECT 8497T. Two methodologies were compared for in terms of their modeling, sensitivity analysis, and optimization abilities. All experiments were performed accordingly to box-behnken design (BBD), and the generated data was analyzed using RSM and PSO. The sensitivity analysis performed by both methods has given comparative results. Based on the correlation coefficient, the model developed with PSO was found to be superior to the model developed with RSM. The result shows that PSO gives a better pigmentation yield with optimal fermentation concentration. Penerbit UTM Press 2018 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/84731/1/SitiMariyamShamsuddin2019_ComparisonofParticleSwarmOptimizationandResponse.pdf Suhaimi, Siti Nurulasilah and Shamsuddin, Siti Mariyam and Ahmad, Wan Azlina and Hasan, Shafaatunnur and Venil, Chidambaram Kulandaisamy (2018) Comparison of particle swarm optimization and response surface methodology in fermentation media optimization of flexirubin production. Jurnal Teknologi, 8 (2). pp. 53-60. ISSN 2180-3722 https://dx.doi.org/10.11113/jt.v81.10766 DOI:10.11113/jt.v81.10766
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Suhaimi, Siti Nurulasilah
Shamsuddin, Siti Mariyam
Ahmad, Wan Azlina
Hasan, Shafaatunnur
Venil, Chidambaram Kulandaisamy
Comparison of particle swarm optimization and response surface methodology in fermentation media optimization of flexirubin production
description At present, response surface methodology (RSM) is the most preferred method for fermentation media optimization. However, in the last two decades, artificial intelligence algorithm has become one of the most efficient methods for empirical modelling and optimization. One of the popular developed approaches is Particle Swarm Optimization (PSO), which is used in optimizing a problem. This paper focuses on comparative studies between RSM and PSO in fermentation media optimization for the production of flexirubin production using Chryseobacterium artocarpi CECT 8497T. Two methodologies were compared for in terms of their modeling, sensitivity analysis, and optimization abilities. All experiments were performed accordingly to box-behnken design (BBD), and the generated data was analyzed using RSM and PSO. The sensitivity analysis performed by both methods has given comparative results. Based on the correlation coefficient, the model developed with PSO was found to be superior to the model developed with RSM. The result shows that PSO gives a better pigmentation yield with optimal fermentation concentration.
format Article
author Suhaimi, Siti Nurulasilah
Shamsuddin, Siti Mariyam
Ahmad, Wan Azlina
Hasan, Shafaatunnur
Venil, Chidambaram Kulandaisamy
author_facet Suhaimi, Siti Nurulasilah
Shamsuddin, Siti Mariyam
Ahmad, Wan Azlina
Hasan, Shafaatunnur
Venil, Chidambaram Kulandaisamy
author_sort Suhaimi, Siti Nurulasilah
title Comparison of particle swarm optimization and response surface methodology in fermentation media optimization of flexirubin production
title_short Comparison of particle swarm optimization and response surface methodology in fermentation media optimization of flexirubin production
title_full Comparison of particle swarm optimization and response surface methodology in fermentation media optimization of flexirubin production
title_fullStr Comparison of particle swarm optimization and response surface methodology in fermentation media optimization of flexirubin production
title_full_unstemmed Comparison of particle swarm optimization and response surface methodology in fermentation media optimization of flexirubin production
title_sort comparison of particle swarm optimization and response surface methodology in fermentation media optimization of flexirubin production
publisher Penerbit UTM Press
publishDate 2018
url http://eprints.utm.my/id/eprint/84731/1/SitiMariyamShamsuddin2019_ComparisonofParticleSwarmOptimizationandResponse.pdf
http://eprints.utm.my/id/eprint/84731/
https://dx.doi.org/10.11113/jt.v81.10766
_version_ 1662754299424276480
score 13.211869

Similar Items