@ARTICLE { Rsds2259,
author = {Suraj, Zbigniew}, 
title = {Discovering Concurrent Data Models and Decision Algorithms from Data: A Rough Set Approach}, 
journal = {International Journal on Artificial Intelligence and Machine Learning}, 
volume = IRSI, 
pages = {29--34}, 
publisher = {ICGST}, 
month = {December}, 
year = 2004, 
note = {A Special Issue on Rough/Fuzzy Sets and Applications, A. E. Hassanien (Ed.)}, 
abstract = {The aim of the paper is to present a new methodology of discovering concurrent data models and decision algorithms from experimental data tables. This methodology is mainly based on rough sets, fuzzy sets, and Petri nets. The presented methodology is illustrated by two intuitive examples.}, 
keywords = {rough sets, fuzzy sets, concurrent models, Petri nets, knowledge discovery, data mining, system decomposition, approximate reasoning, }, 
}