Comparison studies of LS_SVM and SVM on modeling for fermentation processes

Authors:
Xuejin Gao;Pu Wang;Yongsheng Qi;Aijun Yan;Huiqing Zhang;Yanjie Gong
Affiliations:
College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China;College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China;College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China and College of Information Engineering, Inner Mongolia University of Technology, Huhhot ...;College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China;College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China;College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
Venue:
ICNC'09 Proceedings of the 5th international conference on Natural computation
Year:
2009

Citing 12
Cited 0

The nature of statistical learning theory

The nature of statistical learning theory
Genetic algorithms + data structures = evolution programs (3rd ed.)

Genetic algorithms + data structures = evolution programs (3rd ed.)
Least Squares Support Vector Machine Classifiers

Neural Processing Letters
Evolutionary computation

Evolutionary computation
Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models

Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
Support Vector Machines: Theory and Applications (Studies in Fuzziness and Soft Computing)

Support Vector Machines: Theory and Applications (Studies in Fuzziness and Soft Computing)
Support vector machines for automated recognition of obstructive sleep apnea syndrome from ECG recordings

IEEE Transactions on Information Technology in Biomedicine
Support Vector Machine Training for Improved Hidden Markov Modeling

IEEE Transactions on Signal Processing
Modeling crossover-induced linkage in genetic algorithms

IEEE Transactions on Evolutionary Computation
A Generic Framework for Constrained Optimization Using Genetic Algorithms

IEEE Transactions on Evolutionary Computation
An AM Radio Receiver Designed With a Genetic Algorithm Based on a Bacterial Conjugation Genetic Operator

IEEE Transactions on Evolutionary Computation
An overview of statistical learning theory

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

The SVM needs use approximation accuracy Ɛ, however the LS_SVM (least square support vector machine) doesn't need Ɛ. According to these characteristics, this paper studies the fitting and generalization capabilities of models that LS_SVM and SVM establishes for the penicillin fermentation processes respectively. An improved GA selects the parameter values for LS_SVM and SVM respectively. The experiment shows the model based on LS_SVM possesses the strong capabilities of fitting and generalization. If Ɛ is too large, the capabilities of fitting and generalization of model based on SVM are not high; if Ɛ is too small, the capabilities of fitting and generalization are relatively high, but the modeling process demands more long time. So, the LS_SVM is more suitable for modeling in fermentation processes.