Parameters selection and application of support vector machines based on particle swarm optimization algorithm

Kongzhi Lilun Yu Yingyong/Control Theory and Applications

Volumn 23, Issue 5, 2006, Pages

  Shao, Xin Guang ^a   Yang, Hui Zhong ^a   Chen, Gang ^a  

^a JIANGNAN UNIVERSITY   (China)

Author keywords

Parameters selection; Particle swarm optimization; Polyacrylonitrile; Soft sensor; Support vector machines

Indexed keywords

FITNESS FUNCTION; PARAMETERS SELECTION; PARTICLE SWARM OPTIMIZATION; SOFT SENSOR; SUPPORT VECTOR MACHINES;

COMPUTER SIMULATION; EVOLUTIONARY ALGORITHMS; MOLECULAR WEIGHT; POLYACRYLONITRILES;

OPTIMIZATION;

EID: 33846507069     PISSN: 10008152     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (11)

1. VAPNIK V N. The Nature of Statistical Learning Theory[M]. New York: Springer-Verlag, 1995.
2. SMOLA A J, SCHOLKOPF B. A tutorial on support vector regression[R]. NeuroCOLT2 Technical Report NC2-TR-1998-030.
3. SANCHEZ A D. Advanced support vector machines and kernel methods[J]. Neurocomputing, 2003, 55(1): 5-20.
4. CHAPPELLE O, VAPNIK V, BOUSQUET O, et al. Choosing multiple parameters for support vector machines[J]. Machine Learning, 2002, 46(1): 131-160.
5. CHEN Pengwei, WANG Jungying, LEE Hahnming. Model selection of SVMs using GA approach[C]//Proc of 2004 IEEE Int Joint Conf on Neural Networks. Piscataway, NJ: IEEE Press, 2004: 2035-2040.
6. ZHENG Chunhong, JIAO Licheng. Automatic parameters selection for SVM based on GA[C]//Proc of the 5th World Congress on Intelligent Control and Automation. Piscataway, NJ: IEEE Press, 2004: 1869-1872.
7. KENNEDY J, EBERHART R. Particle swarm optimization[C]//Proc of IEEE Int Conf on Neural Networks, Perth, Australia. Piscataway, NJ: IEEE Press, 1995: 1942-1948.
8. EBERHART R, KENNEY J. A new optimizer using particle swarm theory[C]//Proc of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan. Piscataway, NJ: IEEE Press, 1995: 39-43.
9. VANDEN B F, ENGELBRECHT A P. Training product uhit networks using cooperative particle swarm optimizers[C]]//Proc of the Third Genetic and Evolutionary Computation Conference (GECCO), San Francisco, USA. Piscataway, NJ: IEEE Press, 2001: 126-132.
10. YANG Huizhong, ZHANG Suzheng, TAO Zhenlin. The application of soft measurement hybrid model for the quality performance of polyacrylohitrile[J]. Control and Instruments in Chemical Industry, 2002, 29(6): 11-13.
11. SHAO Xinguang, YANG Huizhong, SHI Chenxi. Chemical process data modeling based on ε-insensitive support vector regression[J]. Journal of Southeast University, 2004, 34(Suppl): 215-218.