Realization of XOR by SIRMs Connected Fuzzy Inference Method
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
On the equivalence of single input type fuzzy inference methods
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Implementation of fuzzy Q-learning based on modular fuzzy model and parallel structured learning
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
On the monotonicity of fuzzy-inference methods related to T-S inference method
IEEE Transactions on Fuzzy Systems - Special section on computing with words
Nonlinear function approximation using fuzzy functional SIRMs inference model
AIKED'12 Proceedings of the 11th WSEAS international conference on Artificial Intelligence, Knowledge Engineering and Data Bases
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SIRMs connected fuzzy inference method adopting emphasis and suppression
Fuzzy Sets and Systems
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Yubazaki have proposed a ldquosingle input rule modules connected type fuzzy reasoning method (SIRMs method)rdquo in which its final output is obtained by summarizing the product of importance degree and inference result from single input fuzzy rule modules. This paper proposes a ldquofunctional-type SIRMs method,rdquo which is an extended version of the SIRMs method, and clarifies the relationship between the Takagi--Sugeno (T--S) reasoning method and the functional-type SIRMs method. The functional-type SIRMs method can be shown to be transformed to the T--S reasoning method, but generally the conversion to functional-type SIRMs method from the T--S reasoning method is impossible. It is shown, however, that the T--S reasoning method can be transformed to the functional-type SIRMs method when the T--S reasoning method fills some conditions. For this reason, it is shown that the functional-type SIRMs method is the subset of the T--S reasoning method.