Fuzzy Concepts in Expert Systems
Computer
On fuzzy implication operators
Fuzzy Sets and Systems
Multi-criteria ranking of components according to their priority for inspection
Fuzzy Sets and Systems
Methodology of linguistics evaluation in risk situations using fuzzy techniques
Fuzzy Sets and Systems
An algorithm to compute the degree of match in fuzzy systems
Fuzzy Sets and Systems
Linguistic recognition system based on approximate reasoning
Information Sciences: an International Journal
Dynamical fuzzy reasoning and its application to system modeling
Fuzzy Sets and Systems
What are fuzzy rules and how to use them
Fuzzy Sets and Systems - Special issue dedicated to the memory of Professor Arnold Kaufmann
Completeness and consistency conditions for learning fuzzy rules
Fuzzy Sets and Systems
Human Problem Solving
A proposal on reasoning methods in fuzzy rule-based classification systems
International Journal of Approximate Reasoning
A fuzzy classifier with ellipsoidal regions
IEEE Transactions on Fuzzy Systems
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Fuzzy production rules have been successfully applied to represent uncertainty in a knowledge-based system. The knowledge organized as a knowledge base is static. On the other hand, a real system such as the stock market is dynamic in nature. Therefore we need a strategy to reflect the dynamic nature of a system when we make reasoning with a knowledge-based system.This paper proposes a strategy of dynamic reasoning that can be used to takes account the dynamic behavior of decision-making with the knowledge-based system consisted of fuzzy rules. A degree of match (DM) between actual input information and antecedent of a rule is represented by a value in interval [0, 1]. Weights of relative importance of attributes in a rule are obtained by the AHP (Analytic Hierarchy Process) method. Then these weights are applied as exponents for the DM, and the DMs in a rule are combined, with the Min operator, into a single DM for the rule. In this way, the importance of attributes of a rule, which can be changed from time to time, can be reflected to reasoning in knowledge-based system with fuzzy rules.With the proposed reasoning procedure, a decision maker can take his judgment on the given decision environment into a static knowledge base with fuzzy rules when he makes decision with the knowledge base. This procedure can be automated as a pre-processing system for fuzzy expert systems. Thereby the quality of decisions could be enhanced.