Abstract
Fuzzy interpolative reasoning techniques can reduce the complexity of a sparse fuzzy rule-based system. In this paper, we present a new fuzzy interpola tive reasoning method via cutting and transformations techniques for sparse fuzzy rule-based systems. It produces more reasonable reasoning consequences than the ones presented in [1] and [3]. The proposed method provides a useful way to deal with fuzzy interpolative reasoning in sparse fuzzy rule-based systems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hsiao, W.H., Chen, S.M., Lee, C.H.: A new interpolative reasoning method in sparse rule-based systems. Fuzzy Sets and Systems 93, 17–22 (1998)
Huang, Z.H., Shen, Q.: A new fuzzy interpolative reasoning method based on center of gravity. In: Proceedings of the 2003, IEEE International Conference on Fuzzy Systems, vol. 1, pp. 25–30 (2003)
Koczy, L.T., Hirota, K.: Approximate reasoning by linear rule interpolation and general approximation. International Journal of Approximate Reasoning 9, 197–225 (1993)
Koczy, L.T., Hirota, K.: Interpolative reasoning with insufficient evidence in sparse fuzzy rule bases. Information Sciences 71, 169–201 (1993)
Koczy, L.T., Hirota, K.: Size reduction by interpolation in fuzzy rule bases. IEEE Transactions Systems, Man and Cybernetics 27, 14–25 (1997)
Yan, S., Mizumoto, M., Qiao, W.Z.: Reasoning conditions on Koczy’s interpolative reasoning method in sparse fuzzy rule bases. Fuzzy Sets and Systems 75, 63–71 (1995)
Huang, Z.H., Shen, Q.: Fuzzy Interpolative Reasoning via scale and move Transformations. IEEE Transactions on Fuzzy Systems 14, 340–359 (2006)
Mizumoto, M., Zimmermann, H.-J.: Comparison of fuzzy reasoning methods. Fuzzy Sets and Systems 15, 253–283 (1982)
Zadeh, L.A.: Interpolative reasoning in fuzzy logic and neural network theory. In: Proceedings of the First International Conference on Fuzzy Systems (1992)
Qiao, W.Z., Mizumoto, M., Yan, S.Y.: An improvement to Koczy and Hirotas interpolative reasoning in sparse fuzzy rule bases. International Journal of Approximate Reasoning 15, 185–201 (1996)
Shi, Y., Mizumoto, M.: Some considerations on Koczy’s interpolative reasoning method. In: Proceedings of the 1995 IEEE International Conference on Fuzzy Systems, pp. 2117–2122. IEEE Computer Society Press, Los Alamitos (1995)
Tikk, D., Baranyi, P.: Comprehensive analysis of a new fuzzy rule interpolation method. IEEE Transactions on Fuzzy Systems 8, 281–296 (2000)
Yam, Y., Koczy, L.T.: Cartesian representation for fuzzy interpolation. In: Proceedings of the 37th Conference on Decision and Control, pp. 2936–2937 (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Ko, YK., Chen, SM. (2007). Fuzzy Interpolative Reasoning Via Cutting and Transformations Techniques. In: Okuno, H.G., Ali, M. (eds) New Trends in Applied Artificial Intelligence. IEA/AIE 2007. Lecture Notes in Computer Science(), vol 4570. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73325-6_24
Download citation
DOI: https://doi.org/10.1007/978-3-540-73325-6_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73322-5
Online ISBN: 978-3-540-73325-6
eBook Packages: Computer ScienceComputer Science (R0)