By Topic

Knowledge representation using fuzzy Petri nets-revisited

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Manoj, T.V. ; Kerala Univ., Trivandrum ; Leena, J. ; Soney, R.B.

In the paper by S. Chen et al. (see ibid., vol.2, no.3, p.311-19, 1990), the authors proposed an algorithm which determines whether there exists an antecedent-consequence relationship from a fuzzy proposition d s to proposition dj and if the degree of truth of proposition ds is given, then the degree of truth of proposition dj can be evaluated. The fuzzy reasoning algorithm proposed by S. Chen et al. (1990) was found not to be working with all types of data. We propose: (1) a modified form of the algorithm, and (2) a concept of hierarchical fuzzy Petri nets for data abstraction

Published in:

Knowledge and Data Engineering, IEEE Transactions on  (Volume:10 ,  Issue: 4 )