DocumentCode
1994849
Title
Fuzzy Petri nets
Author
Cheng, Paxton ; Forward, Kevin
Author_Institution
Dept. of Electr. & Electron. Eng., Melbourne Univ., Vic., Australia
Volume
2
fYear
1997
fDate
27-23 May 1997
Firstpage
402
Abstract
Proposes a new model of a fuzzy Petri net and an algorithm to generate such a network automatically. As an example of the application of the fuzzy Petri net, it is used to classify the Iris data set. Although there are extensive examples of neural network-based classifiers in the literature, they all share the undesirable characteristic of a long learning time. We attempt to remedy this problem by using a totally different architecture, and the resulting Petri net attains comparable performance with conventional systems with just a few seconds of training
Keywords
Petri nets; fuzzy set theory; learning (artificial intelligence); mathematics computing; neural net architecture; pattern classification; Iris data set classification; fuzzy Petri net generation algorithm; learning time; neural net architecture; neural network-based classifier; performance; training; Data mining; Error analysis; Fuzzy logic; Fuzzy sets; Iris; Neural networks; Performance analysis; Petri nets; Solar power generation; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge-Based Intelligent Electronic Systems, 1997. KES '97. Proceedings., 1997 First International Conference on
Conference_Location
Adelaide, SA
Print_ISBN
0-7803-3755-7
Type
conf
DOI
10.1109/KES.1997.619416
Filename
619416
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