Abstract
In the paper we develop a new method for designing and reduction of neuro-fuzzy systems. The method is based on the concept of the weighted triangular norms. In subsequent stages we reduce number of inputs, number of rules and number of antecedents. Simulation results are given.
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Alonso, J.M., Cordon, O., Guillaume, S., Magdalena, L.: Highly Interpretable Linguistic Knowledge Bases Optimization: Genetic Tuning versus Solis-Wetts. Looking for a good interpretability-accuracy trade-off. In: Proc. of the 2007 IEEE Int. Conf. on Fuzzy Systems, pp. 1–6 (2007)
Amaral, T.G., Crisostomo, M.M.: An Approach to Improve the Interpretability of Neuro-Fuzzy Systems. In: Proc. of the 2006 IEEE Int. Conf. on Fuzzy Systems, pp. 1843–1850 (2006)
Casillas, J., Cordon, O., Herrera, F., Magdalena, L. (eds.): Interpretability Issues in Fuzzy Modeling. Springer, Heidelberg (2003)
Czabanski, R.: Neuro-Fuzzy Modelling Based on a Deterministic Annealing Approach. Int. J. Appl. Math. Comput. Sci. 15(4), 561–576 (2005)
Czogała, E., Łȩski, J.: Fuzzy and Neuro-Fuzzy Intelligent Systems. Physica-Verlag, Heidelberg (2000)
Gorzałczany, M.: Computational Intelligence Systems and Applications: Neuro-Fuzzy and Fuzzy Neural Synergisms. Springer, Heidelberg (2002)
Guillaume, S.: Designing fuzzy inference systems from data: An interpretability-oriented review. IEEE Trans. Fuzzy Syst. 9(3), 426–443 (2001)
Kumar, M., Stoll, R., Stoll, N.: A robust design criterion for interpretable fuzzy models with uncertain data. IEEE Trans. Fuzzy Syst. 14(2), 314–328 (2006)
Łȩski, J., Henzel, N.: A Neuro-Fuzzy System Based on Logical Interpretation of If-then Rules. Int. J. Appl. Math. Comput. Sci. 10(4), 703–722 (2000)
Łȩski, J.: A Fuzzy If-Then Rule-Based Nonlinear Classifier. Int. J. Appl. Math. Comput. Sci. 13(2), 215–223 (2003)
Manley-Cooke, P., Razaz, M.: An efficient approach for reduction of membership functions and rules in fuzzy systems. In: Proc. of the 2007 IEEE Int. Conf. on Fuzzy Systems, pp. 1–6 (2007)
Riid, A., Rustern, E.: Interpretability of Fuzzy Systems and Its Application to Process Control. In: Proc. of the 2007 IEEE Int. Conf. on Fuzzy Systems, pp. 1–6 (2007)
Rutkowski, L.: Flexible Neuro-Fuzzy Systems. Kluwer Academic Publishers, Dordrecht (2004)
Rutkowski, L., Cpałka, K.: Flexible neuro-fuzzy systems. IEEE Trans. Neural Networks 14(3), 554–574 (2003)
Yager, R.R., Filev, D.P.: Essentials of fuzzy modelling and control. John Wiley & Sons, Chichester (1994)
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Cpalka, K., Rutkowski, L. (2008). An Application of Weighted Triangular Norms to Complexity Reduction of Neuro-fuzzy Systems. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_21
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DOI: https://doi.org/10.1007/978-3-540-69731-2_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69572-1
Online ISBN: 978-3-540-69731-2
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