An online self-organizing scheme for parsimonious and accurate fuzzy neural networks

International Journal of Neural Systems

Volumn 20, Issue 5, 2010, Pages 389-403

  Wang, Ning ^a   Er, Meng Joo ^b   Meng, Xian Yao ^a   Li, Xiang ^c  

^a DALIAN MARITIME UNIVERSITY   (China)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c SINGAPORE INSTITUTE OF MANUFACTURING TECHNOLOGY   (Singapore)

Author keywords

extended Kalman filter (EKF); Fuzzy Neural Network (FNN); growing criterion; linear least squares (LLS); online self organizing

Indexed keywords

APPROXIMATION ACCURACY; BENCH-MARK PROBLEMS; CHAOTIC TIME SERIES PREDICTION; FUNCTION APPROXIMATION; FUZZY NEURAL NETWORK (FNN); GROWING CRITERION; HIDDEN NEURONS; HIDDEN UNITS; LEARNING PHASE; LINEAR LEAST SQUARES; NETWORK STRUCTURES; NON-LINEAR DYNAMIC SYSTEMS; NOVEL STRUCTURES; ONLINE LEARNING; OPTIMAL PARAMETER; OPTIMIZATION OF PARAMETERS; PARAMETER LEARNING; PRUNING STRATEGY; SELF ORGANIZING; SELF-ORGANIZING SCHEME; SIMULATION RESULT; STATE-OF-THE-ART METHODS; STRUCTURE-LEARNING; TWO STAGE;

APPROXIMATION ALGORITHMS; CHAOTIC SYSTEMS; COMPUTER SIMULATION; EXTENDED KALMAN FILTERS; FUZZY FILTERS; LEARNING ALGORITHMS; NONLINEAR DYNAMICAL SYSTEMS; OPTIMIZATION; PARAMETER ESTIMATION; POSITION CONTROL; QUEUEING NETWORKS; SPEECH RECOGNITION; SURFACE RECONSTRUCTION;

FUZZY NEURAL NETWORKS;

ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; FUZZY LOGIC; ONLINE SYSTEM;

ARTIFICIAL INTELLIGENCE; FUZZY LOGIC; NEURAL NETWORKS (COMPUTER); ONLINE SYSTEMS;

EID: 77958042224     PISSN: 01290657     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0129065710002486     Document Type: Article

References (75)

1. H. Adeli and S. L. Hung, An adaptive conjugate gradient learning algorithm for effective training of multilayer neural networks, Applied Mathematics and Computation 62(1) (1994) 81-102.
2. H. Adeli and X. Jiang, Neuro-fuzzy logic model for freeway work zone capacity estimation, Journal of Transportation Engineering 129(5) (2003) 484-493. (Pubitemid 37164325)
3. H. Adeli and X. Jiang, Dynamic fuzzy wavelet neural network model for structural system identification, Journal of Structural Engineering 132(1) (2006) 102-111.
4. H. Adeli and A. Karim, Neural network model for optimization of cold-formed steel beams, Journal of Structural Engineering, ASCE 123(11) (1997) 1535-1543.
5. H. Adeli and H. S. Park, Counter propagation neural network in structural engineering, Journal of Structural Engineering, ASCE 121(8) (1995a) 1205-1212.
6. H. Adeli and H. S. Park, A neural dynamics model for structural optimization - Theory, Computers and Structures 57(3) (1995b) 383-390.
7. H. Adeli and H. S. Park, Optimization of space structures by neural dynamics, Neural Networks 8(5) (1995c) 769-781.
8. M. Asaduzzaman, M. Shahjahan and K. Murase, Faster training using fusion of activation functions for feed forward neural networks, International Journal of Neural Systems 19(6) (2009) 437-448.
9. Y. Benedic, P. Wira and J. Merckle, A new method for the re-implementation of threshold logic functions with cellular neural networks, International Journal of Neural Systems 18(4) (2008) 293-303.
10. E. P. Carden and J. M. W. Brownjohn, Fuzzy clustering of stability diagrams for vibration-based structural health monitoring, Computer-Aided Civil and Infrastructure Engineering 23(5) (2008) 360-372.
11. C. T. Chao, Y. J. Chen and C. C. Teng, Simplification of fuzzy-neural systems using similarity analysis, IEEE Transactions on System, Man, Cybernetics, Part B, Cybernetics 26(2) (1996) 344-354.
12. L. C. Chao, Fuzzy logic model for determining minimum bid markup, Computer-Aided Civil and Infrastructure Engineering 22(6) (2007) 449-460.
13. S. Chen, C. F. N. Cowan and P. M. Grant, Orthogonal least squares learning algorithm for radial basis function network, IEEE Transactions on Neural Networks 2(2) (1991) 1411-1423.
14. K. B. Cho and B. H. Wang, Radial basis function based adaptive fuzzy systems and their applications to system identification and prediction, Fuzzy Sets and Systems 83(3) (1996) 325-339.
15. M. A. Christodoulou and C. Kontogeorgou, Collision avoidance in commercial aircraft free fight, via neural networks and non-linear programming, International Journal of Neural Systems 18(5)(2008) 371-387.
16. M. J. Er and S. Q. Wu, A fast learning algorithm for parsimonious fuzzy neural systems, Fuzzy Sets and Systems 126(3) (2002) 337-351.
17. A. Fatehi and K. Kenichi Abe, Flexible structure multiple modeling using irregular self-organizing maps neural network, International Journal of Neural Systems 18(3) (2008) 233-256.
18. Y. Gao and M. J. Er, Online adaptive fuzzy neural identification and control of a class of MIMO nonlinear systems, IEEE Transactions on Fuzzy Systems 11(4) (2003) 12-32.
19. Y. Gao and M. J. Er, NARMAX time series model prediction: Feedforward and recurrent fuzzy neural network approaches, Fuzzy Sets and Systems 150(2) (2005a) 331-350.
20. Y. Gao and M. J. Er, An intelligent adaptive control scheme for postsurgical blood pressure regulation, IEEE Transactions on Neural Networks 16(2) (2005b) 475-483.
21. S. Ghosh-Dastidar and H. Adeli, Wavelet-clusteringneural network model for freeway incident detection, Computer-Aided Civil and Infrastructure Engineering 18(5) (2003) 325-338.
22. S. Ghosh-Dastidar and H. Adeli, Improved spiking neural networks for EEG classification and epilepsy and seizure detection, Integrated Computer-Aided Engineering 14(3) (2007) 187-212.
23. S. Ghosh-Dastidar, H. Adeli and N. Dadmehr, Mixed-band wavelet-chaos-neural network methodology for epilepsy and epileptic seizure detection, IEEE Transactions on Biomedical Engineering 54(9) (2007) 1545-1551.
24. A. M. A. Haidar, A. Mohamed, M. Al-Dabbagh, A. Aini Hussain and M. Masoum, An intelligent load shedding scheme using neural networks and neurofuzzy, International Journal of Neural Systems 19(6) (2009) 473-479.
25. G. B. Huang, P. Saratchandran and N. Sundararajan, An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks, IEEE Transactions on System, Man, Cybernetics, Part B, Cybernetics 34(6) (2004) 2284-2292.
26. G. B. Huang, P. Saratchandran and N. Sundararajan, A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation, IEEE Transactions on Neural Networks 16(1) (2005) 57-67.
27. H. T. Huynh, Y. Won and J. J. Kim, An improvement of extreme learning machine for compact single-hidden-layer feedforward neural networks, International Journal of Neural Systems 18(5) (2008) 433-441.
28. T. Isokawa, H. Nishimura, N. Kamiura and N. Matsui, Associative memory in quaternionic hopfield neural network, International Journal of Neural Systems 18(2) (2008) 135-145.
29. J. S. R. Jang, ANFIS: Adaptive-network-based fuzzy inference system, IEEE Transactions on Systems, Man, Cybernetics 23(3) (1993) 665-684.
30. J. S. R. Jang and C. T. Sun, Functional equivalence between radial basis function networks and fuzzy inference systems, IEEE Transactions on Neural Networks 4(1) (1993) 156-159.
31. J. S. R. Jang, C. T. Sun and E. Mizutani, Neuro- Fuzzy and Soft Computing (Prentice-Hall, Englewood 1997 Cliffs, NJ).
32. X. Jiang and H. Adeli, Pseudospectra, MUSIC, and dynamic wavelet neural network for damage detection of highrise buildings, International Journal for Numerical Methods in Engineering 71(5) (2007) 606-629.
33. X. Jiang and H. Adeli, Dynamic fuzzy wavelet neuroemulator for nonlinear control of irregular highrise building structures, International Journal for Numerical Methods in Engineering 74(7) (2008) 1045-1066.
34. X. L. Jin and H. Doloi, Modelling risk allocation decision-making in PPP projects using fuzzy logic, Computer-Aided Civil and Infrastructure Engineering 24(7) (2009) 509-524.
35. T. D. Jorgensen, B. P. Haynes and C. C. F. Norlund, Pruning artificial neural networks using neural complexity measures, International Journal of Neural Systems 18(5) (2008) 389-403.
36. C. F. Juang and C. T. Lin, An on-line selfconstructing neural fuzzy inference network and its applications, IEEE Transactions on Fuzzy Systems 6(1) (1998) 12-32.
37. V. Kadirkamanathan and M. Niranjan, A function estimation approach to sequential learning with neural networks, Neural Computing 5(6) (1993) 954-975.
38. A. Karim and H. Adeli, CONSCOM: An OO construction scheduling and change management system, Journal of Construction Engineering and Management 125(5) (1999) 368-376.
39. A. Karim and H. Adeli, Comparison of the fuzzy - Wavelet RBFNN freeway incident detection model with the California algorithm, Journal of Transportation Engineering 128(1) (2002) 21-30.
40. A. Khashman, Blood cell identification using a simple neural network, International Journal of Neural Systems 18(5) (2008) 453-458.
41. T. Kimura and T. Ikeguchi, An optimum strategy for dynamic and stochastic packet routing problems by chaotic neurodynamics, Integrated Computer-Aided Engineering 14(4) (2007) 307-322.
42. G. Leng, T. M. McGinnity and G. Prasad, An approach for on-line extraction of fuzzy rules using a self-organising fuzzy neural network, Fuzzy Sets and Systems 150(2) (2005) 211-243.
43. N. Y. Liang, G. B. Huang, P. Saratchandran and N. Sundararajan, A fast and accurate online sequential learning algorithm for feedforward networks, IEEE Transactions on Neural Networks 17(6) (2006) 1411-1423.
44. J. Menke and T. T. Martinez, Improving supervised learning by adapting the problem to the learner, International Journal of Neural Systems 19(1) (2009) 1-9.
45. S. Mitra and Y. Hayashi, Neuro-fuzzy rule generation: Survey in soft computing framework, IEEE Transactions on Neural Networks 11(3) (2000) 748-768.
46. T. Nakashima, Y. Yokota, H. Ishibuchi and G. Schaefer, Learning fuzzy If-Then rules for pattern classification with weighted training patterns, in Proceedings of the 4th Conference on European Society for Fuzzy Logic and Technology, (eds.) E. Montseny and P. Sobrevilla (Barcelona, Spain, 2005), (2005) 1064-1069.
47. Y. Nomura, H. Furuta and M. Hiorkane, An integrated fuzzy control system for structural vibrations, Computer-Aided Civil and Infrastructure Engineering 22(4) (2007) 306-316.
48. A. Panakkat and H. Adeli, Recurrent neural network for approximate earthquake time and location prediction using multiple seismicity indicators, Computer-Aided Civil and Infrastructure Engineering 24(4) (2009) 280-292.
49. A. Pande and M. Abdel-Aty, A computing approach using probabilistic neural networks for instantaneous appraisal of rear-end crash risk, Computer-Aided Civil and Infrastructure Engineering 23(7) (2008) 549-559.
50. H. S. Park and H. Adeli, Distributed neural dynamics algorithms for optimization of large steel structures, Journal of Structural Engineering, ASCE 123(7) (1997) 880-888. (Pubitemid 127663695)
51. W. Pedrycz, R. Rai and J. Zurada, Experienceconsistent modeling for radial basis function neural networks, International Journal of Neural Systems 18(4) (2008) 279-292.
52. K. Perusich, Using fuzzy cognitive maps to identify multiple causes in troubleshooting systems, Integrated Computer-Aided Engineering 15(2) (2008) 197-206.
53. J. Platt, A resource-allocating network for function interpolation, Neural Computing 3(2) (1991) 213-225.
54. G. Puscasu and B. Codres, Nonlinear system identification based on internal recurrent neural networks, International Journal of Neural Systems 19(2) (2009) 115-125.
55. G. G. Rigatos, Adaptive fuzzy control with output feedback for H-infinity tracking of SISI nonlinear systems, International Journal of Neural Systems 18(4) (2008) 305-320.
56. I. Rojas, H. Pomares, J. L. Bernier, J. Ortega, B. Pino, F. J. Pelayo and A. Prieto, Time series analysis using normalized PG-RBF network with regression weights, Neurocomputing 42(1) (2002) 267-285.
57. H. J. Rong, N. Sundararajan, G. B. Huang and P. Saratchandran, Sequential Adaptive Fuzzy Inference System (SAFIS) for nonlinear system identification and prediction, Fuzzy Sets and Systems 157(9) (2006) 1260-1275.
58. C. Sabourin, K. Madani and O. Bruneau, Autonomous biped gait pattern based on fuzzy- CMAC neural networks, Integrated Computer- Aided Engineering 14(2) (2007) 173-186.
59. M. Salmeron, J. Ortega, C. G. Puntonet and A. Prieto, Improved RAN sequential prediction using orthogonal techniques, Neurocomputing 41(1) (2001) 153-172.
60. A. Samant and H. Adeli, Enhancing neural network incident detection algorithms using wavelets, Computer-Aided Civil and Infrastructure Engineering 16(4) (2001) 239-245.
61. J. F. Smith and T. H. Nguyen, Autonomous and cooperative robotic behavior based on fuzzy logic and genetic programming, Integrated Computer- Aided Engineering 14(2) (2007) 141-159.
62. A. Stathopoulos, L. Dimitriou and T. Tsekeris, Fuzzy modeling approach for combined forecasting of urban traffic flow, Computer-Aided Civil and Infrastructure Engineering 23(7) (2008) 521-535.
63. M. Sugeno and G. T. Kang, Structure identification of fuzzy model, Fuzzy Sets and Systems 28(1) (1988) 15-33.
64. Z. L. Sun, K. F. Au and T. M. Choi, A neuro-fuzzy inference system through integration of fuzzy logic and extreme learning machines, IEEE Transactions on System, Man, Cybernetics, Part B, Cybernetics 37(5) (2007) 1321-1331.
65. S. Suresh, N. Kannan, N. Sundararajan and P. Saratchandran, Neural adaptive control for vibration suppression in composite fin-tip of aircraft, International Journal of Neural Systems 18(3) (2008) 219-231.
66. T. Takagi and I. Hayashi, NN-driven fuzzy reasoning, International Journal of Approximation Reasoning 5(3) (1991) 191-212.
67. V. Torra, A review of the construction of hierarchical fuzzy systems, International Journal of Intelligent Systems 17(5) (2002) 531-543. (Pubitemid 34491735)
68. J. R. Villar, E. de la Cal and J. Sedano, A fuzzy logic based efficient energy saving approach for domestic heating systems, Integrated Computer-Aided Engineering 16(2) (2009) 151-163.
69. I. Villaverde, M. Grana and A. d'Anjou, Morphological neural networks and vision based simultaneous localization and mapping, Integrated Computer- Aided Engineering 14(4) (2007) 355-363.
70. N. Wang, M. J. Er and X. Y. Meng, A fast and accurate online self-organizing scheme for parsimonious fuzzy neural networks, Neurocomputing 72(16) (2009) 3818-3829.
71. L. X. Wang, Adaptive Fuzzy Systems and Control: Design and Stability Analysis (Prentice-Hall, Englewood Cliffs, NJ, 1994).
72. S. Q. Wu and M. J. Er, Dynamic fuzzy neural networks - A novel approach to function approximation, IEEE Transactions on System, Man, Cybernetics, Part B, Cybernetics 30(2) (2000) 358-364.
73. S. Q. Wu, M. J. Er and Y. Gao, A fast approach for automatic generation of fuzzy rules by generalized dynamic fuzzy neural networks, IEEE Transactions on Fuzzy Systems 9(4) (2001) 578-594.
74. L. Yingwei, N. Sundararajan and P. Saratchandran, A sequential learning scheme for function approximation using minimal Radial Basis Function (RBF) neural networks, Neural Computing 9(2) (1997) 461-478. (Pubitemid 127635401)
75. L. Yingwei, N. Sundararajan and P. Saratchandran, Performance evaluation of a sequential minimal Radial Basis Function (RBF) neural network learning algorithm, IEEE Transactions on Neural Networks 9(2) (1998) 308-318.