A SVR-based multiple modeling algorithm for antibiotic fermentation process using FCM

Yaofeng Xue; Jingqi Yuan

doi:10.1007/11427469_110

A SVR-based multiple modeling algorithm for antibiotic fermentation process using FCM

Yaofeng Xue^*
, Jingqi Yuan

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

Abstract

A multiple modeling algorithm for antibiotic fermentation process based on fuzzy c-means (FCM) and support vector regression (SVR) is proposed. By analyzing the features of antibiotic fermentation, the mechanism of multiple modeling of the bioprocess is presented. Using FCM clustering method, the bioprocess is classified into several work states and sub-models. Then, taking advantage of the generalization properties of SVR, the multiple model of bioprocess is established and the proposed algorithm is described. Experimental data of industrial penicillin production is used to validate the model.

Original language	English
Pages (from-to)	691-696
Number of pages	6
Journal	Lecture Notes in Computer Science
Volume	3498
Issue number	III
DOIs	https://doi.org/10.1007/11427469_110
State	Published - 2005
Externally published	Yes
Event	Second International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005 - Chongqing, China Duration: 30 May 2005 → 1 Jun 2005

Access to Document

10.1007/11427469_110

Cite this

@article{b78476b1a87f4a4f8ccaf844f4b7af27,

title = "A SVR-based multiple modeling algorithm for antibiotic fermentation process using FCM",

abstract = "A multiple modeling algorithm for antibiotic fermentation process based on fuzzy c-means (FCM) and support vector regression (SVR) is proposed. By analyzing the features of antibiotic fermentation, the mechanism of multiple modeling of the bioprocess is presented. Using FCM clustering method, the bioprocess is classified into several work states and sub-models. Then, taking advantage of the generalization properties of SVR, the multiple model of bioprocess is established and the proposed algorithm is described. Experimental data of industrial penicillin production is used to validate the model.",

author = "Yaofeng Xue and Jingqi Yuan",

year = "2005",

doi = "10.1007/11427469\_110",

language = "英语",

volume = "3498",

pages = "691--696",

journal = "Lecture Notes in Computer Science",

issn = "0302-9743",

publisher = "Springer Science and Business Media Deutschland GmbH",

number = "III",

note = "Second International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005 ; Conference date: 30-05-2005 Through 01-06-2005",

}

TY - JOUR

T1 - A SVR-based multiple modeling algorithm for antibiotic fermentation process using FCM

AU - Xue, Yaofeng

AU - Yuan, Jingqi

PY - 2005

Y1 - 2005

N2 - A multiple modeling algorithm for antibiotic fermentation process based on fuzzy c-means (FCM) and support vector regression (SVR) is proposed. By analyzing the features of antibiotic fermentation, the mechanism of multiple modeling of the bioprocess is presented. Using FCM clustering method, the bioprocess is classified into several work states and sub-models. Then, taking advantage of the generalization properties of SVR, the multiple model of bioprocess is established and the proposed algorithm is described. Experimental data of industrial penicillin production is used to validate the model.

AB - A multiple modeling algorithm for antibiotic fermentation process based on fuzzy c-means (FCM) and support vector regression (SVR) is proposed. By analyzing the features of antibiotic fermentation, the mechanism of multiple modeling of the bioprocess is presented. Using FCM clustering method, the bioprocess is classified into several work states and sub-models. Then, taking advantage of the generalization properties of SVR, the multiple model of bioprocess is established and the proposed algorithm is described. Experimental data of industrial penicillin production is used to validate the model.

UR - https://www.scopus.com/pages/publications/24944510726

U2 - 10.1007/11427469_110

DO - 10.1007/11427469_110

M3 - 会议文章

AN - SCOPUS:24944510726

SN - 0302-9743

VL - 3498

SP - 691

EP - 696

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

IS - III

T2 - Second International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005

Y2 - 30 May 2005 through 1 June 2005

ER -

A SVR-based multiple modeling algorithm for antibiotic fermentation process using FCM

Abstract

Access to Document

Other files and links

Fingerprint

Cite this