Fuzzy Rules Interpolation for Sparse Fuzzy Rule-Based Systems Based on Interval Type-2 Gaussian Fuzzy Sets and Genetic Algorithms
- 12 November 2012
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Fuzzy Systems
- Vol. 21 (3), 412-425
- https://doi.org/10.1109/tfuzz.2012.2226942
Abstract
In this paper, we present a new method for fuzzy rules interpolation for sparse fuzzy rule-based systems based on interval type-2 Gaussian fuzzy sets and genetic algorithms. First, we present a method to deal with the interpolation of fuzzy rules based on interval type-2 Gaussian fuzzy sets. We also prove that the proposed method guarantees to produce normal interval type-2 Gaussian fuzzy sets. Then, we present a method to learn optimal interval type-2 Gaussian fuzzy sets for sparse fuzzy rule-based systems based on genetic algorithms. We also apply the proposed fuzzy rules interpolation method and the proposed learning method to deal with multivariate regression problems and time series prediction problems. The experimental results show that the proposed fuzzy rules interpolation method using the optimally learned interval type-2 Gaussian fuzzy sets gets higher average accuracy rates than the existing methods.Keywords
This publication has 29 references indexed in Scilit:
- Adaptive Fuzzy InterpolationIEEE Transactions on Fuzzy Systems, 2011
- Adaptive fuzzy interpolation with prioritized component candidatesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Weighted Fuzzy Interpolative Reasoning Based on Weighted Increment Transformation and Weighted Ratio Transformation TechniquesIEEE Transactions on Fuzzy Systems, 2009
- Interval Type-2 Fuzzy Logic Systems Made SimpleIEEE Transactions on Fuzzy Systems, 2006
- Interpolation with function space representation of membership functionsIEEE Transactions on Fuzzy Systems, 2006
- Fuzzy rule interpolation for multidimensional input spaces with applications: a case studyIEEE Transactions on Fuzzy Systems, 2005
- Comprehensive analysis of a new fuzzy rule interpolation methodIEEE Transactions on Fuzzy Systems, 2000
- Representing membership functions as points in high-dimensional spaces for fuzzy interpolation and extrapolationIEEE Transactions on Fuzzy Systems, 2000
- An improvement to Kóczy and Hirota's interpolative reasoning in sparse fuzzy rule basesInternational Journal of Approximate Reasoning, 1996
- Generating fuzzy rules by learning from examplesIEEE Transactions on Systems, Man, and Cybernetics, 1992