Paper Info
Title
Definition And Adaptation Of Weighted Fuzzy Logic Programs
Abstract
Fuzzy logic programming has been lately used as a general framework for representing and handling imprecise knowledge. In this paper, we de. ne the syntax and the semantics of definite weighted fuzzy logic programs, which extend definite fuzzy logic programs by allowing the inclusion of different significance weights in the individual atoms that make up the antecedent of a fuzzy logic rule. The weights add expressiveness to a fuzzy logic program and allow the determination of the level up to which an atom in the antecedent of a rule may affect the truth value of its consequent. In describing the semantics of definite weighted fuzzy logic programs we introduce the notion of the generalized weighted fuzzy conjunction operator, which can be regarded as a weighted t-norm based aggregation. We determine the properties of generalized weighted fuzzy conjunction operators and provide several examples. A methodology for constructing generalized weighted fuzzy conjunction operators using generator functions of existing t-norms is also introduced. Finally, a method for setting up a parametric weighted fuzzy logic program and automatically adapting the weights of its rules using a numerical dataset is developed.
Year
DOI
Venue
2009
10.1142/S0218488509005759
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS
Keywords
Field
DocType
Fuzzy logic programming, fuzzy logic, logic programming, triangular norms, weighted conjunctions, knowledge adaptation, rule extraction
Discrete mathematics,T-norm fuzzy logics,Defuzzification,Fuzzy classification,Fuzzy set operations,Fuzzy logic,Artificial intelligence,Fuzzy Control Language,Fuzzy associative matrix,Fuzzy number,Mathematics,Machine learning
Journal
Volume
Issue
ISSN
17
1
0218-4885
Citations 
PageRank 
References 
1
0.35
21
Authors
3
Name
Order
Citations
PageRank
Alexandros Chortaras111612.31
Giorgos Stamou2120076.88
Andreas Stafylopatis337853.30