Soft sensor modeling based on DE-LSSVM

Huagong Xuebao/Journal of Chemical Industry and Engineering (China)

Volumn 59, Issue 7, 2008, Pages 1681-1685

  Lin, Bihua ^a   Gu, Xingsheng ^a  

^a EAST CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

4 carboxybenzaldehyde; Differential evolution; Least squares support vector machine; Soft sensor

Indexed keywords

ARTIFICIAL INTELLIGENCE; CURVE FITTING; DETECTORS; DIGITAL ARITHMETIC; EVOLUTIONARY ALGORITHMS; IMAGE RETRIEVAL; LEARNING ALGORITHMS; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; SENSORS; STANDARDIZATION; STANDARDS; VECTORS;

4-CARBOXYBENZALDEHYDE (4-CBA); DIFFERENTIAL EVOLUTION (DE); INDUSTRIAL PROCESSING; LEAST SQUARES SUPPORT VECTOR MACHINE (LS SVM); MACHINE-LEARNING; PARAMETER SELECTION; SOFT SENSING; SOFT-SENSOR MODELING; STATISTICAL THEORY; SUPPORT VECTOR MACHINE (SVM); TEREPHTHALIC ACID (TPA);

SUPPORT VECTOR MACHINES;

EID: 48049085873     PISSN: 04381157     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (15)

1. Vapnik V N. The Nature of Statistical Learning Theory. New York: Springer-Verlag, 1995
2. Cortes C, Vapnik V. Support-vector networks. Machine Learning, 1995, 20: 273-297
3. Suykens J A K, Vandewalle J. Least squares support vector machines classifiers. Neural Networks Letters, 1999, 19(3): 293-300
4. Liu Ruilan, Mou Shengjing, Chu Jian, et al. Modeling soft sensor based on support vector machine and particle swarm optimization algorithms. Control Theory and Applications, 2006, 23(6): 895-900
5. Chen Pengwei, Wang Jungying, Lee Hahnming. Model Selection of Neural Networks. Piscataway: IEEE Press, 2004: 2035-2040
6. Storn R, Price K. Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces: Technical Report[R]. Berkeley: International Computer Science Institute, 1995
7. Ali M M, Torn A. Population set-based global optimization algorithms: some modifications and numerical studies. Computers and Operations Research, 2004, 31(10): 1703-1725
8. Liu Bo, Wang Ling, Jin Yihui. Advances in differential evolution. Control and Decision, 2007, 22(7): 721-730
9. Zhou Yanping, Gu Xingsheng. Advances in differential evolution. Control and Instruments in Chemical Industry, 2007, 34(3): 1-5
10. Kaelo P, Ali M M. A numerical study of some modified differential evolution algorithms. European Journal of Operational Research, 2006, 169: 1176-1184
11. Zhong Xuan, Wang Shuqing. On-line soft sensing for end point of naphtha based on neural network. Journal of Chemical Industry and Engineering (China), 1998, 49(2): 251-255
12. Liu Jianxin, Bai Peng. Technology of terephthalic acid and its production. Science and Technology Chemical Industry, 2000, 8(3): 64-67
13. Raghavendrachar P, Ramachandran S. Liquid-phase catalytic oxidation of p-xylene. Ind. Eng. Chem. Res., 1992, 31(2): 453-462
14. Hu Yongyou, Gu Yong. Research on soft-sensing modeling of 4-CBA based on BPNN. Chinese Journal of Scientific Instrument, 2003, 24(3): 226-230
15. Zheng Xiaoxia, Qian Feng. Soft sensor modeling based on PCA and support vector machines. Journal of System Simulation, 2006, 18(3): 739-741