Genetic optimization of type-2 fuzzy weight adjustment for backpropagation in ensemble neural network

Studies in Computational Intelligence

Volumn 451, Issue , 2013, Pages 159-171

  Gaxiola, Fernando ^a   Melin, Patricia ^a   Valdez, Fevrier ^a  

^a TIJUANA INSTITUTE OF TECHNOLOGY   (Mexico)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84870558211     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-33021-6_13     Document Type: Article

References (36)

1. Abiyev, R.H.: A Type-2 Fuzzy Wavelet Neural Network for Time Series Prediction. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds.) IEA/AIE 2010, Part III. LNCS, vol. 6098, pp. 518-527. Springer, Heidelberg (2010
2. Barbounis, T.G., Theocharis, J.B.: Locally Recurrent Neural Networks for Wind Speed Prediction using Spatial Correlation. Information Sciences 177(24), 5775-5797 (2007
3. Beale, E.M.L.: A Derivation of Conjugate Gradients. In: Lootsma, F.A. (ed.) Numerical Methods for Nonlinear Optimization, pp. 39-43. Academic Press, London (1972
4. Casasent, D., Natarajan, S.: A Classifier Neural Net with Complex-Valued Weights and Square-Law Nonlinearities. Neural Networks 8(6), 989-998 (1995
5. Castillo, O., Melin, P.: A review on the design and optimization of interval type-2 fuzzy controllers. Applied Soft Computing 12(4), 1267-1278 (2012
6. Castro, J., Castillo, O., Melin, P., Rodríguez-Díaz, A.: A Hybrid Learning Algorithm for a Class of Interval Type-2 Fuzzy Neural Networks. Information Sciences 179(13), 2175-2193 (2009
7. Castro, J., Castillo, O., Melin, P., Mendoza, O., Rodríguez- Díaz, A.: An Interval Type-2 Fuzzy Neural Network for Chaotic Time Series Prediction with Cross-Validation and Akaike Test. Soft Computing for Intelligent Control and Mobile Robotics, 269-285 (2011
8. Cazorla, M., Escolano, F.: Two Bayesian Methods for Junction Detection. IEEE Transaction on Image Processing 12(3), 317-327 (2003
9. De Wilde, O.: The Magnitude of the Diagonal Elements in Neural Networks. Neural Networks 10(3), 499-504 (1997
10. Draghici, S.: On the Capabilities of Neural Networks using Limited Precision Weights. Neural Networks 15(3), 395-414 (2002
11. Feuring, T.: Learning in Fuzzy Neural Networks. In: IEEE International Conference on Neural Networks, vol. 2, pp. 1061-1066 (1996
12. Fletcher, R., Reeves, C.M.: Function Minimization by Conjugate Gradients. Computer Journal 7, 149-154 (1964
13. Gedeon, T.: Additive Neural Networks and Periodic Patterns. Neural Networks 12(4-5), 617-626 (1999
14. Hagan, M.T., Demuth, H.B., Beale, M.H.: Neural Network Design, p. 736. PWS Publishing, Boston (1996
15. Hagras, H.: Type-2 Fuzzy Logic Controllers: A Way Forward for Fuzzy Systems in Real World Environments. In: IEEE World Congress on Computational Intelligence, pp. 181-200 (2008
16. Haupt, R., Haupt, S.: Practical Genetic Algorithms, p. 272. John Wiley and Sons, Inc., Hoboken (2004
17. Ishibuchi, H., Morioka, K., Tanaka, H.: A Fuzzy Neural Network with Trapezoid Fuzzy Weights, Fuzzy Systems. In: IEEE World Congress on Computational Intelligence, vol. 1, pp. 228-233 (1994
18. Ishibuchi, H., Tanaka, H., Okada, H.: Fuzzy Neural Networks with Fuzzy Weights and Fuzzy Biases. In: IEEE International Conference on Neural Networks, vol. 3, pp. 1650-1655 (1993
19. Jang, J.S.R., Sun, C.T., Mizutani, E.: Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, p. 614. Prentice Hall (1997
20. Kamarthi, S., Pittner, S.: Accelerating Neural Network Training using Weight Extrapolations. Neural Networks 12(9), 1285-1299 (1999
21. Karnik, N., Mendel, J.: Applications of Type-2 Fuzzy Logic Systems to Forecasting of Time-Series. Information Sciences 120(1-4), 89-111 (1999
22. Martinez, G., Melin, P., Bravo, D., Gonzalez, F., Gonzalez, M.: Modular Neural Networks and Fuzzy Sugeno Integral for Face and Fingerprint Recognition. Advances in Soft Computing 34, 603-618 (2006
23. Melin, P.: Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition, pp. 1-204. Springer (2012
24. Meltser, M., Shoham, M., Manevitz, L.: Approximating Functions by Neural Networks: A Constructive Solution in the Uniform Norm. Neural Networks 9(6), 965-978 (1996
25. Moller, M.F.: A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning. Neural Networks 6, 525-533 (1993
26. Monirul Islam, M.D., Murase, K.: A New Algorithm to Design Compact Two-Hidden-Layer Artificial Neural Networks. Neural Networks 14(9), 1265-1278 (2001
27. Neville, R.S., Eldridge, S.: Transformations of Sigma-Pi Nets: Obtaining Reflected Functions by Reflecting Weight Matrices. Neural Networks 15(3), 375-393 (2002
28. Phansalkar, V.V., Sastry, P.S.: Analysis of the Back-Propagation Algorithm with Momentum. IEEE Transactions on Neural Networks 5(3), 505-506 (1994
29. Powell, M.J.D.: Restart Procedures for the Conjugate Gradient Method. Mathematical Programming 12, 241-254 (1977
30. Pulido, M., Melin, P., Castillo, O.: Genetic Optimization of Ensemble Neural Networks for Complex Time Series Predicition. In: IJCNN, pp. 202-206 (2011
31. Salazar, P.A., Melin, P., Castillo, O.: A New Biometric Recognition Technique Based on Hand Geometry and Voice Using Neural Networks and Fuzzy Logic. Soft Computing for Hybrid Intelligent Systems, 171-186 (2008
32. Sanchez, D., Melin, P.: Modular Neural Network with Fuzzy Integration and its Optimization Using Genetic Algorithms for Human Recognition based on Iris, Ear and Voice Biometrics. Soft Computing for Recognition Based on Biometrics, 85-102 (2010
33. Sepúlveda, R., Castillo, O., Melin, P., Montiel, O.: An Efficient Computational Method to Implement Type-2 Fuzzy Logic in Control Applications. Analysis and Design of Intelligent Systems using Soft Computing Techniques, 45-52 (2007
34. Valdez, F., Melin, P., Parra, H.: Parallel Genetic Algorithms for Optimization of Modular Neural Networks in Pattern Recognition. In: IJCNN, pp. 314-319 (2011
35. Yam, J., Chow, T.: A Weight Initialization Method for Improving Training Speed in Feedforward Neural Network. Neurocomputing 30(1-4), 219-232 (2000
36. Yeung, D., Chan, P., Ng, W.: Radial Basis Function Network Learning using Localized Generalization Error Bound. Information Sciences 179(19), 3199-3217 (2009