Feature selection using double parallel feedforward neural networks and particle swarm optimization

2007 IEEE Congress on Evolutionary Computation, CEC 2007

Volumn , Issue , 2007, Pages 692-696

  Huang, Rui ^a   He, Mingyi ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DOUBLE PARALLEL FEEDFORWARD NEURAL NETWORK (DPFNN); SINGLE-LAYER FEEDFORWARD NEURAL NETWORK (SFNN);

ERROR ANALYSIS; FEEDFORWARD NEURAL NETWORKS; PARALLEL PROGRAMMING; PARTICLE SWARM OPTIMIZATION (PSO); PROBLEM SOLVING;

FEATURE EXTRACTION;

EID: 51849110463     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2007.4424538     Document Type: Conference Paper

References (24)

1. L. M. Belue and K. W. Bauer, "Determining input features for multilayer perceptrons," Neurocomputing, vol. 7, pp. 111-121, 1995.
2. K. W. Bauer, S. G. Alsing, and K. A. Greene, "Feature screening using signal-to-noise ratios," Neurocomputing, vol. 31, pp. 29-44, 2000.
3. R. Setiono and H. Liu, "Neural-network feature selector," IEEE Trans. Neural Networks, vol. 8, no. 3, pp. 654-662, 1997.
4. A. Verikas and M. Bacauskiene, "Feature selection with neural net-works," Pattern Recognition Letters, vol. 23, pp. 1323-1335, 2002.
5. G.-B. Huang, Q.-Y. Zhu, and C.-K. Siew, "Extreme learning machine: A new learning scheme of feedforward neural networks," in Proc. 2004 International Joint Conference on Neural Networks, Budapest, Hungary, 2004, pp. 985-990.
6. Z. Guo and R. E. Uhrig, "Using genetic algorithms to select inputs for neural networks," in Proc. International Workshop on Combinations of Genetic Algorithms and Neural Networks, Los Alamitos, CA, USA, 1992, pp. 223-234.
7. V. Maniezzo, "Genetic evolution of the topology and weight distribution of neural networks," IEEE Trans. Neural Networks, vol. 5, no. 1, pp. 39-53, 1994.
8. X. Yao, "Evolving artificial neural networks," Proc. the IEEE, vol. 87, no. 9, pp. 1423-1447, 1999.
9. J. M. Yang and C. Y. Cao, "A robust evolutionary algorithm for training neural networks," Neural Computing and Application, vol. 10, no. 3, pp. 214-230, 2001.
10. R. C. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Proc. 6th International Symposium on Micromachine and Human Science, Nagoya, Japan, 1995, pp. 39-43.
11. J. Kennedy and R. C. Eberhart, "Particle swarm optimization," in Proc. IEEE International Conference on Neural Networks, Perth, Australia, 1995, pp. 1942-1948.
12. R. C. Eberhart and Y. Shi, "Evolving artificial neural networks," in Proc. International Conference on Neural Networks and Brain, Beijing, China, 1998, pp. 5-13.
13. C. Zhang, H. Shao, and Y. Li, "Particle swarm optimisation for evolving artificial neural network," in Proc. IEEE International Conference on Systems, Man, and Cybernetics, Nashville, TN, USA, 2000, pp. 2487-2490.
14. C.-F. Juang and Y.-C. Liou, "On the hybrid of genetic algorithm and particle swarm optimization for evolving recurrent neural network," in Proc. International Joint Conference on Neural Networks, Budapest, Hungary, 2004, pp. 2285-2289.
15. Z. Wang, G. L. Durst, R. C. Eberhart, and et al., "Particle swarm optimization and neural network application for qsar," in Proc. 3rd IEEE International Workshop on High Performance Computational Biology, Santa Fe, NM, USA, 2004.
16. Y. Liu, Z. Qin, Z. Xu, and et al., "Feature selection with particle swarms," in Proc. Computational and Information Science, Shanghai, China, 2004, pp. 425-430.
17. M. He, "Theory, application and related problems of double parallel feedforward neural networks," Ph.D. dissertation, Xidian University, Xi'an, China, 1993.
18. M. He and Z. Bao, Neural network and information processing system: limited precision design theory. Xi'an, China: Northwestern Polytech-nical University publisher, 1998.
19. M. He and J. Xia, "High dimensional multispectral image fusion: classification by neural network," in Proc. SPIE, Image Processing and Pattern Recognition in Remote Sensing, vol. 4898, Hangzhou, China, 2003, pp. 36-43.
20. M. He and R. Huang, "Feature selection for hyperspectral data classification using double parallel feedforward neural networks," in Proc. 1st International Conference on Natural Computation and 2nd International Conference on Fuzzy Systems and Knowledge Discovery, Changsha, China, 2005, pp. 58-62.
21. Y. Shi and R. C. Eberhart, "Empirical study of particle swarm optimization," in Proc. Congress on Evolutionary Computation, Piscataway, USA, 1999, pp. 1945-1950.
22. M. He and R. Huang, "Feature selection using a new hybrid pso and ga algorithm for classification of hyperspectral data," in Proc. 2006 International Symposium on AI, Beijing, China, 2006.
23. L. C. Molina, L. Belanche, and A. Nebot, "Feature selection algorithms: a survey and experimental evaluation," in Proc. International Conference on Data Mining, Maebashi City, Japan, 2002, pp. 306-313.
24. D. J. Newman, S. Hettich, C. L. Blake, and et al, "Uci repository of machine learning databases," 1998, university of California, Department of Information and Computer Science.