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Fuzzy Pruning Based LS-SVM Modeling Development for a Fermentation Process
Joint Authors
Zhang, Wei
Liu, Dengfeng
Xu, Bao-guo
Xiong, Weili
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-27
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Due to the complexity and uncertainty of microbial fermentation processes, data coming from the plants often contain some outliers.
However, these data may be treated as the normal support vectors, which always deteriorate the performance of soft sensor modeling.
Since the outliers also contaminate the correlation structure of the least square support vector machine (LS-SVM), the fuzzy pruning method is provided to deal with the problem.
Furthermore, by assigning different fuzzy membership scores to data samples, the sensitivity of the model to the outliers can be reduced greatly.
The effectiveness and efficiency of the proposed approach are demonstrated through two numerical examples as well as a simulator case of penicillin fermentation process.
American Psychological Association (APA)
Xiong, Weili& Zhang, Wei& Liu, Dengfeng& Xu, Bao-guo. 2014. Fuzzy Pruning Based LS-SVM Modeling Development for a Fermentation Process. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1034005
Modern Language Association (MLA)
Xiong, Weili…[et al.]. Fuzzy Pruning Based LS-SVM Modeling Development for a Fermentation Process. Abstract and Applied Analysis No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-1034005
American Medical Association (AMA)
Xiong, Weili& Zhang, Wei& Liu, Dengfeng& Xu, Bao-guo. Fuzzy Pruning Based LS-SVM Modeling Development for a Fermentation Process. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1034005
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1034005