A comparative assessment of measures of similarity of fuzzy values
Fuzzy Sets and Systems
Fuzzy Sets and Systems
Approximate reasoning with time
Fuzzy Sets and Systems
Uncertainty, fuzzy logic, and signal processing
Signal Processing - Special issue on fuzzy logic in signal processing
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Pattern recognition using type-II fuzzy sets
Information Sciences—Informatics and Computer Science: An International Journal
Comparison of type-2 fuzzy values with satisfaction function
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Correlation coefficient for type-2 fuzzy sets: Research Articles
International Journal of Intelligent Systems
Similarity-based approximate reasoning: methodology and application
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Fuzzy Systems
Fuzzy logic and self-referential reasoning: a comparative study with some new concepts
Artificial Intelligence Review
Hi-index | 12.05 |
Representation and manipulation of the vague concepts of partially true knowledge in the development of machine intelligence is a wide and challenging field of study. How to extract of approximate facts from vague and partially true statements has drawn significant attention from researchers in the fuzzy information processing. Furthermore, handling uncertainty from this incomplete information has its own necessity. This study theoretically examines a formal method for representing and manipulating partially true knowledge. This method is based on the similarity measure of type-2 fuzzy sets, which are directly used to handle rule uncertainties that type-1 fuzzy sets cannot. The proposed type-2 similarity-based reasoning method is theoretically defined and discussed herein, and the reasoning results are applied to show the usefulness with the comparison of the general fuzzy sets.