Modular neural networks with applications to pattern profiling problems

Neurocomputing

Volumn 72, Issue 10-12, 2009, Pages 2093-2100

  Chris Tseng, H ^a   Almogahed, Bassam ^a  

^a SAN JOSE STATE UNIVERSITY   (United States)

Author keywords

Modular design; Neural networks; Pattern recognition; Soft computing; Time series prediction

Indexed keywords

AIRCRAFT TRAJECTORIES; ARTIFICIAL NEURAL NETWORKS; COMPUTATION TIME; DESIGN COMPLEXITY; MODULAR APPROACHES; MODULAR DESIGN; MODULAR LEARNING; MODULAR NEURAL NETWORKS; MODULARIZED; NEURO-FUZZY LEARNING; NON-LINEAR PROBLEMS; PATTERN RECOGNITION PROBLEMS; PREDICTION PERFORMANCE; TIME-SERIES PREDICTION; TWO STAGES;

AIRCRAFT; DECOMPOSITION; DESIGN; EDUCATION; LINEARIZATION; PATTERN RECOGNITION; SOFT COMPUTING;

NEURAL NETWORKS;

AIRCRAFT; ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; FEASIBILITY STUDY; FUZZY SYSTEM; GENETIC ALGORITHM; NONLINEAR SYSTEM; ONLINE ANALYSIS; PATTERN RECOGNITION; PREDICTION; PRIORITY JOURNAL; STATISTICAL ANALYSIS; TIME SERIES ANALYSIS;

EID: 67349110175     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2008.10.020     Document Type: Article

References (39)

1. H.L. Teodorescu, A. Kandel, L.C. Jain, Soft-computing in Human-related Sciences, June 1999.
2. L.C. Jain, C.W. De Silva, C.W. de Silva, Intelligent Adaptive Control Industrial applications, CRC Press, Boca Raton, 1998.
3. Chris Tseng H., and Chi C. Aircraft anti-lock brake system (ABS) with and neural networks and fuzzy logic. Journal of Guidance, and Control and Dynamics, AIAA (October 1995) 1113-1118
4. Jacobs R.A., and Jordan M.I. Learning piecewise control strategies in a modular neural network. IEEE Transactions on Systems, Man, and Cybernetics 23 (1993) 337-345
5. Sharma S.K., Irwin G.W., Tokhi M.O., and McLoone S.F. Learning soft computing control strategies in a modular neural network architecture. Engineering Applications of Artificial Intelligence 16 5-6 (2003) 395-405
6. Jiang N., Zhao Z., and Ren L. Design of structural modular neural networks with genetic algorithm. Advances in Engineering Software 34 1 (2003) 17-24
7. Auda G., and Kamel M. Modular neural networks: a survey. International Journal of Neural Systems 9 2 (1999) 129-151
8. Chris Tseng H., and Chi C.W. Modular intelligent control. Advances in Fuzzy Theory and Technology III (1995)
9. Mitra S., Mitra P., and Pal S.K. Evolutionary modular design of rough knowledge-based network using fuzzy attributes. Neurocomputing 36 1-4 (2001) 45-66
10. Chris Tseng H. Control with word: the modular approach. Information Sciences 134 1-4 (2001) 111-133
11. C.W. Chi, S.T.C. Hsia, H. Chris Tseng, Adaptive aggregation of modular fuzzy control, IEEE International Conference on Systems, Man, and Cybernetics, Orlando, Florida, 1997.
12. Siljak D.D. Decentralized Control of Complex Systems (1990), Elsevier
13. M. Su, M. Basu, in: Proceedings of the International Joint Conference on Neural Networks, IJCNN '01, vol. 3, 15-19 July 2001, pp. 2159-2164.
14. Jordan M.I., and Jacobs R.A. A competitive modular connectionist architecture, in: Advances in Neural Information Processing Systems vol. 3 (1991), Morgan Kaufmann, San Mateo, CA pp. 767-773
15. Osherson D.N., Weinstein S., and Stoli M. Modular learning. Computational Neuroscience (1990) 369-377
16. Jordan M.I., and Jacobs R.A. Task decomposition through competition in a modular connectionist architecture: the what and where vision tasks. Cognitive Science 15 (1991) 219-250
17. Simon H. Neural Networks, A comprehensive Foundation (1994), Macmillan College Publishing Company, New York, NY
18. F. Azam, Biologically inspired modular neural networks, Doctor of Philosophy, May 2000.
19. Auda G., and Kamel H. Modular neural network classifiers: a comparative study. Journal of Intelligent and Robotic Systems 21 (1998) 117-129
20. Lu B.-L., and Ito M. Task decomposition and module combination based on class relations: a modular neural network for pattern classification. IEEE Transaction on Neural Networks 10 5 (September 1999)
21. R. Jacobs, Task decomposition through competition in a modular connectionist architecture, Ph.D. Thesis, University of Massachusetts, Amherst, MA, USA 1990.
22. G. Bartfei, Hierarchical clustering with art neural networks, in: World Congress on Computational Intelligence, vol. 2, Florida, USA, 1994, pp. 940-944.
23. De Bollivier M., Gallinari P., and Thiria S. Cooperation of neural nets and task decomposition. International Joint Conference on Neural Networks 2 (1991) 573-576
24. Auda G., and Kamel M. Modular neural networks classifiers: a comparative study. Journal of Intelligent and Robotic Systems 21 (1998) 117-129
25. Raafat H., and Rashwan M. A tree structured neural network. International Conference on Document Analysis and Recognition 93 (1993) 939-942
26. G. Auda, M. Kamel, H. Raafat, Modular neural network architecture for classification, in: IEEE International Conference on Neural Networks, ICNN'96, vol. 2, Washington, DC, 1996, pp. 1279-1284.
27. Jacobs R.A., Jordan M.I., and Barto A. Task decomposition through competition in a modular connectionist architecture: the what and where vision tasks. Neural Computation 3 (1991) 79-87
28. Jacobs R.A., Jordan M.I., Nowlan S.J., and Hinton G.E. Adaptive mixtures of local experts. Neural Computation 3 1 (1991) 79-87
29. Sammon Jr. J. A nonlinear mapping for data structure analysis. IEEE Transactions on Computers C 18 (1969) 401-409
30. Tsai H., Tai H., and Reynolds A. An ART2-BP Neural Net and Its Application to Reservoir Engineering (1994), IEEE, USA
31. H. Hackbarth, J. Mantel, Modular connectionist structure for 100-word recognition, in: International Joint Conference on Neural Networks, vol. 2, Seattle, USA, 1991, pp. 845-849.
32. G. Auda, M. Kamel, H. Raafat, Voting schemes for cooperative neural network classifiers, in: IEEE International Conference on Neural Networks, ICNN'95, vol. 3, Perth, Australia, November 1995, pp. 1240-1243.
33. Auda G., and Kamel M. CMNN: cooperative modular neural network. IEEE Conference on Neural Networks 1 (1997) 226-231
34. Garcia-Pedrajas N., Hervas-Martinez C., and Ortiz-Boyer D. Cooperative coevolution of artificial neural network ensembles for pattern classification. IEEE Transactions on Evolutionary Computation 9 3 (2005) 271-302
35. Melin P., and Castillo O. Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems (2005), Springer, Berlin
36. A. Blansché, P. Gançarski, J.J. Korczak, MACLAW: a modular approach for clustering with local attribute weighting, vol. 27, issue 11, Elsevier B.V., August 2006, pp. 1299-1306.
37. Cantu-Paz E., and Kamath C. An empirical comparison of combinations of evolutionary algorithms and neural networks for classification problems. IEEE Systems, Man, and Cybernetics Society 35 5 (2005) 915-927
38. Jang J.S.R. ANFIS: adaptive-network-based fuzzy inference systems. IEEE Transactions on Systems, Man, and Cybernetics 23 (1993) 665-685
39. H. Chris Tseng, A. Epshteyn, Modular design for neural computing problems, in: Eighth International Conference on Natural Computing, Salt Lake City, July 18-19, 2007.