Title :
A generalized fuzzy Petri net model
Author :
Pedrycz, Witold ; Gomide, Fernando
Author_Institution :
Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada
fDate :
11/1/1994 12:00:00 AM
Abstract :
The paper proposes a new model of Petri nets based on the use of logic based neurons. In contrast to the existing generalizations, this approach is aimed at neural-type modeling of the entire concept with a full exploitation of the learning capabilities of the processing units being used there. The places and transitions of the net are represented by OR and AND-type and DOMINANCE neurons, respectively. A correspondence between this model and the previous two-valued counterpart is also revealed. The learning aspects associated with the nets are investigated
Keywords :
Petri nets; fuzzy set theory; learning (artificial intelligence); AND-type neurons; DOMINANCE neurons; OR-type neurons; generalized fuzzy Petri net model; learning capabilities; neural-type modeling; Computational intelligence; Computational modeling; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Intelligent systems; Neurons; Petri nets; Visualization;
Journal_Title :
Fuzzy Systems, IEEE Transactions on
