Sequential Fuzzy Description Logic: Reasoning for Fuzzy Knowledge Bases with Sequential Information

Author(s):  
Norihiro Kamide
2013 ◽  
Vol 12 (1) ◽  
pp. 069-076
Author(s):  
Janusz Szelka ◽  
Zbigniew Wrona

The IT tools that are widely used for aiding information and decision-making tasks in engineering activities include classic database systems, and in the case of problems with poorly-recognised structure – systems with knowledge bases. The uniqueness of these categories of systems allows, however, neither to represent the approximate or imprecise nature of available data or knowledge nor to process fuzzy data. Since so far there have been no solutions related to the use of fuzzy databases or fuzzy knowledge bases in engineering projects, it seems necessary to make an attempt to assess the possible employment of these technologies to aid analytical and decision-making processes.


2017 ◽  
Vol 48 (1) ◽  
pp. 220-242 ◽  
Author(s):  
Fu Zhang ◽  
Z. M. Ma ◽  
Qiang Tong ◽  
Jingwei Cheng

2009 ◽  
Vol 43 (4) ◽  
pp. 187-190 ◽  
Author(s):  
N. A. Korenevsky ◽  
S. A. Gorbatenko ◽  
R. A. Krupchatnikov ◽  
M. I. Lukashov

2003 ◽  
Vol 11 (4) ◽  
pp. 439-461
Author(s):  
A. Carrascal ◽  
D. Manrique ◽  
J. Ríos ◽  
C. Rossi

This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary methods. We have designed a genetic algorithm that automatically builds neuro-fuzzy architectures based on a new indirect encoding method. The neuro-fuzzy architecture represents the fuzzy knowledge base that solves a given problem; the search for this architecture takes advantage of a local search procedure that improves the chromosomes at each generation. Experiments conducted both on artificially generated and real world problems confirm the effectiveness of the proposed approach.


Sign in / Sign up

Export Citation Format

Share Document