@INCOLLECTION { Rsds4981,
author = {Fryc, Barbara and Pancerz, Krzysztof and Suraj, Zbigniew}, 
title = {On approximate Petri nets with fuzzy operators in data classification process}, 
booktitle = {Systemy Wspomagania Decyzji}, 
pages = {53--61}, 
publisher = {Wydawnictwo Uniwersytetu Slaskiego}, 
address = {Katowice, Poland}, 
year = 2009, 
editor = {Wakulicz-Deja, Alicja}, 
isbn = {978-83-920730-6-2}, 
abstract = {In the paper, we present and discuss results of experiments performed on the real-life data by the use of approximate Petri nets (AP-nets) with different fuzzy operators in a data classification process. Moreover, we provide some comments concerning the evaluation of a quality of data classification for different fuzzy operators. Approximate Petri nets have been introduced in 2004, among others, to represent the knowledge for decision making as well as approximate reasoning. This approach is based on the fuzzy set theory and the rough set theory. The main idea of this net model derives from colored Petri nets introduced by K. Jensen and fuzzy Petri nets proposed by S.-M. Chen et al. The AP-net model makes it possible to design and simulate decision making as well as approximate reasoning processes carried out on the basis of the rules extracted automatically from experimental data tables by the use of rough set methods, or provided by domain experts. A decision making mechanism, used in AP-nets, has been based on the fuzzy set theory, especially, it uses fuzzy operations (e.g., fuzzy t-norms, fuzzy s-norms) on the fuzzy sets.}, 
keywords = {decision making, approximate Petri nets, fuzzy sets, fuzzy operations, decision systems, rules, }, 
}