Fuzzy controls under various fuzzy reasoning methods
Information Sciences: an International Journal - Application of Fuzzy Set Theory
International Journal of Approximate Reasoning
Semantics and computation of the generalized modus ponens: the long paper
International Journal of Approximate Reasoning
Neurocomputations in Relational Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy sets in approximate reasoning, part 1: inference with possibility distributions
Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
A comparative assessment of measures of similarity of fuzzy values
Fuzzy Sets and Systems
Fuzzy Sets and Systems
Bidirectional approximate reasoning for rule-based systems using interval-valued fuzzy sets
Fuzzy Sets and Systems
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
On generalized modus ponens with multiple rules and a residuated implication
Fuzzy Sets and Systems - Data bases and approximate reasoning
Automorphisms, negations and implication operators
Fuzzy Sets and Systems - Implication operators
On locally internal monotonic operations
Fuzzy Sets and Systems - Special issue: Preference modelling and applications
On some new classes of implication operators and their role in approximate reasoning
Information Sciences—Informatics and Computer Science: An International Journal
Yager's new class of implications Jf and some classical tautologies
Information Sciences: an International Journal
Distributivity of residual implications over conjunctive and disjunctive uninorms
Fuzzy Sets and Systems
Comparison of fuzzy reasoning methods
Fuzzy Sets and Systems
Fuzzy modus ponens: A new model suitable for applications in knowledge-based systems
International Journal of Intelligent Systems
A comparative study on similarity-based fuzzy reasoning methods
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Simplifying fuzzy rule-based models using orthogonal transformationmethods
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy if... then rule models and their transformation into one another
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Similarity-based approximate reasoning: methodology and application
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Combinatorial rule explosion eliminated by a fuzzy rule configuration
IEEE Transactions on Fuzzy Systems
On the law [p∧q→r]=[(p→r)V(q→r)] in fuzzy logic
IEEE Transactions on Fuzzy Systems
Distributivity and conditional distributivity of a uninorm and a continuous t-conorm
IEEE Transactions on Fuzzy Systems
On dependencies and independencies of fuzzy implication axioms
Fuzzy Sets and Systems
Decision support system for nitrogen fertilization using fuzzy theory
Computers and Electronics in Agriculture
Intersection of Yager's implications with QL and D-implications
International Journal of Approximate Reasoning
Information Sciences: an International Journal
Hi-index | 0.01 |
The two most important models of inferencing in approximate reasoning with fuzzy sets are Zadeh's Compositional Rule of Inference (CRI) and Similarity Based Reasoning (SBR). It is known that inferencing in the above models is resource consuming (both memory and time), since these schemes often consist of discretisation of the input and output spaces followed by computations in each point. Also an increase in the number of rules only exacerbates the problem. As the number of input variables and/or input/output fuzzy sets increases, there is a combinatorial explosion of rules in multiple fuzzy rule based systems. In this paper, given a fuzzy if-then rule base that is used in an SBR inference mechanism, we propose to reduce the number of rules by combining the antecedents of the rules that have the same consequent. We also present some sufficient conditions on the operators employed in SBR inference schemes such that the inferences obtained using the original rule base and the reduced rule base obtained as above are identical. Subsequently, these conditions are investigated and many solutions are presented for some specific SBR inference schemes.