Towards adaptive interpolative reasoning
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Temperature prediction based on fuzzy clustering and fuzzy rules interpolation techniques
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Multi-variable fuzzy forecasting based on fuzzy clustering and fuzzy rule interpolation techniques
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Weighted fuzzy interpolative reasoning for sparse fuzzy rule-based systems
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Fuzzy rule interpolation based on the ratio of fuzziness of interval type-2 fuzzy sets
Expert Systems with Applications: An International Journal
Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on the slopes of fuzzy sets
Expert Systems with Applications: An International Journal
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
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In sparse fuzzy rule-based systems, the fuzzy rule bases are usually incomplete. In this situation, the system may not properly perform fuzzy reasoning to get reasonable consequences. In order to overcome the drawback of sparse fuzzy rule-based systems, there is an increasing demand to develop fuzzy interpolative reasoning techniques in sparse fuzzy rule-based systems. In this paper, we present a new fuzzy interpolative reasoning method via cutting and transformation techniques for sparse fuzzy rule-based systems. It can produce more reasonable results than the existing methods. The proposed method provides a useful way to deal with fuzzy interpolative reasoning in sparse fuzzy rule-based systems.