Paper Info
Title
Qualitative optimization of Fuzzy Causal Rule Bases using Fuzzy Boolean Nets
Abstract
Fuzzy Causal Rule Bases (FCRb) are widely used and are the most important rule bases in Rule Based Fuzzy Cognitive Maps (RB-FCM). However, FCRb are subject to several restrictions that create difficulties in their creation and completion. This paper proposes a method to optimally complete FCRb using Fuzzy Boolean Net properties as qualitative universal approximators. Although the proposed approach focuses on FCRb, it can be generalized to any fuzzy rule base.
Year
DOI
Venue
2007
10.1016/j.fss.2007.04.018
Fuzzy Sets and Systems
Keywords
Field
DocType
qualitative universal approximators,rule base optimization,complete fcrb,fuzzy boolean nets,important rule base,fuzzy causal rule bases,fuzzy causal relations,qualitative optimization,fuzzy rule base,fuzzy cognitive maps,fuzzy boolean,fuzzy cognitive map,rule based
Rule-based system,Fuzzy set operations,Fuzzy cognitive map,Fuzzy logic,Fuzzy set,Artificial intelligence,Fuzzy control system,Fuzzy number,Mathematics,Machine learning,Fuzzy rule
Journal
Volume
Issue
ISSN
158
17
Fuzzy Sets and Systems
Citations 
PageRank 
References 
11
0.68
5
Authors
2
Name
Order
Citations
PageRank
João Paulo Carvalho111017.52
José Tomé2110.68