Abstract
For many practical intelligent decision-making applications, the “curse of dimensionality” is a serious problem; that is, the number of rules increases exponentially along with the number of input variables to the fuzzy inference system (Raju G, Zhou J, Roger A (1991) Int J Control 54(5):1201–1216 [1]).
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G. Raju, J. Zhou, A. Roger, Hierarchical fuzzy control. Int. J. Control 54(5), 1201–1216 (1991)
G. Raju, J. Zhou, Adaptive hierarchical fuzzy controller. IEEE Trans. Syst. Man Cybern. 23(4), 973–980 (1993)
L.T. Kóczy, K. Hirota, L. Muresan, Interpolation in hierarchical fuzzy rule bases, in Proceedings of International Conference on Fuzzy Systems (2000), pp. 471–477
L.T. Kóczy, K. Hirota, L. Muresan, Backward fuzzy rule interpolation. IEEE Trans. Fuzzy Syst. 22(6), 1682–1698 (2014)
S. Jin, R. Diao, C. Quek, Q. Shen, Backward fuzzy rule interpolation with multiple missing values, in Proceedings of IEEE International Conference on Fuzzy Systems (2013), pp. 1–8
S. Jin, R. Diao, C. Quek, Q. Shen, Backward fuzzy interpolation and extrapolation with multiple multi-antecedent rules, in Proceedings of IEEE International Conference on Fuzzy Systems (2012), pp. 1170–1177
Z. Huang, Q. Shen, Fuzzy interpolative reasoning via scale and move transformations. IEEE Trans. Fuzzy Syst. 14(2), 340–359 (2006)
Z. Huang, Q. Shen, Fuzzy interpolation and extrapolation: a practical approach. IEEE Trans. Fuzzy Syst. 16(1), 13–28 (2008)
Z. Huang, Q. Shen, Adaptive fuzzy interpolation. IEEE Trans. Fuzzy Syst. 19(6), 1107–1126 (2011)
D. Wang, X. Zeng, J. Keane, Intermediate variable normalization for gradient descent learning for hierarchical fuzzy system. IEEE Trans. Fuzzy Syst. 17(2), 468–476 (2009)
D. Wang, X. Zeng, J. Keane, Analysis and design of hierarchical fuzzy systems. IEEE Trans. Fuzzy Syst. 7(5), 617–624 (1999)
N. Naik, R. Diao, Q. Shen, Dynamic fuzzy rule interpolation and its application to intrusion detection. IEEE Trans. Fuzzy Syst. (2017)
T. Chen, C. Shang, P. Su, Q. Shen, Induction of accurate and interpretable fuzzy rules from preliminary crisp representation. Knowl. Based Syst. 146, 152–166 (2018)
F. Li, C. Shang, Y. Li, J. Yang, Q. Shen, Fuzzy rule-based interpolative reasoning supported by attribute ranking, IEEE Trans. Fuzzy Syst. (2018)
T. Boongoen, C. Shang, N. Iam-On, Q. Shen, Extending data reliability measure to a filter approach for soft subspace clustering. IEEE Trans. Syst. Man Cybern Part B Cybern 41(6), 1705–1714 (2011)
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Jin, S., Shen, Q., Peng, J. (2019). Hierarchical Bidirectional Fuzzy Rule Interpolation and Rule Base Refinement. In: Backward Fuzzy Rule Interpolation. Springer, Singapore. https://doi.org/10.1007/978-981-13-1654-8_6
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DOI: https://doi.org/10.1007/978-981-13-1654-8_6
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