Research on information requirement of first-order universal implication operators in fuzzy reasoning

Authors:
Fu Lihua;He Huacan
Affiliations:
Department of Computer Science & Engineering, Northwestern Polytechnical University, Xi'an, P.R. China;Department of Computer Science & Engineering, Northwestern Polytechnical University, Xi'an, P.R. China
Venue:
Intelligent information processing II
Year:
2004

Citing 9
Cited 0

Fuzzy sets in approximate reasoning, part 1: inference with possibility distributions

Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
On the specificity of a possibility distribution

Fuzzy Sets and Systems
Default knowledge and measures of specificity

Information Sciences: an International Journal
Fuzzy sets and fuzzy logic: theory and applications

Fuzzy sets and fuzzy logic: theory and applications
Force implication: a new approach to human reasoning

Fuzzy Sets and Systems
A new class of fuzzy implications, axioms of fuzzy implication revisited

Fuzzy Sets and Systems
On global requirements for implication operators in fuzzy modus ponens

Fuzzy Sets and Systems - Special issue on fuzzy modeling and dynamics
Measures of information in generalized constraints

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
On t-norms based measures of specificity

Fuzzy Sets and Systems - Theme: Basic notions

Quantified Score

Hi-index	0.00

Visualization

Abstract

Based on the definition of linear specificity measure, this paper discusses detailedly the conditions on which the first-order universal implication operators satisfy the information boundedness principle in fuzzy reasoning, and gets the corresponding conclusion: when fuzzy propositions have positive measuring errors for their membership grades, first-order universal implication operators satisfy the information boundedness principle only if they are rejecting or restraining correlative; when they have negative ones, the operators satisfy the principle only if they are restraining correlative. This conclusion has important directive meaning for how to give the value of the general correlative coefficient h in practical control application.