Paper Info
Title
Rule-based metainference for crisp-type two-string fuzzy inference systems
Abstract
Two-string inference systems produce output values from activations of recommending rules, as in standard fuzzy inference systems, but also with respect to inhibitions or warnings produced by negative rules. Besides assuring that a forbidden output value must not occur, the crucial point with two-string inference is how the inference results from positive and negative rules can be combined to a single output membership function by which an output value can be calculated. In this paper, a new method for combining the output membership functions of both inference strings to a combined output membership function by means of fuzzy rule-based metainference is proposed. This method generalizes existing methods and additionally provides means to adjust or combine them in a transparent way. Moreover, the possibility of designing new context-dependent or -independent metainference patterns increases flexibility and applicability of two-string fuzzy inference.
Year
DOI
Venue
2014
10.1109/SMC.2014.6974078
Systems, Man and Cybernetics
Keywords
Field
DocType
fuzzy reasoning,fuzzy set theory,knowledge based systems,learning (artificial intelligence),context-dependent metainference,context-independent metainference,crisp-type two-string fuzzy inference system,fuzzy rule-based metainference,single output membership function
Fuzzy classification,Defuzzification,Fuzzy set operations,Computer science,Fuzzy set,Artificial intelligence,Adaptive neuro fuzzy inference system,Fuzzy control system,Type-2 fuzzy sets and systems,Fuzzy number,Machine learning
Conference
ISSN
Citations 
PageRank 
1062-922X
0
0.34
References 
Authors
4
3
Name
Order
Citations
PageRank
Moritz Schneider172.19
Saman Khodaverdian283.96
Jürgen Adamy319239.49