Rough Set Approach to Behavioral Pattern Identification

Issue title: New Frontiers in Scientific Discovery – Commemorating the Life and Work of Zdzislaw Pawlak

Article type: Research Article

Authors: Bazan, Jan G. | Kruczek, Piotr | Bazan-Socha, Stanislawa | Skowron, Andrzej | Pietrzyk, Jacek J.

Affiliations: Institute of Mathematics, University of Rzesz&ów, Rejtana 16A, 35-959 Rzesz&ów, Poland. E-mail: [email protected] | Department of Pediatrics, Collegium Medicum, Jagiellonian University, Wielicka 265, 30-663 Cracow, Poland. E-mial: [email protected] | Department of Internal Medicine, Collegium Medicum, Jagiellonian University, Skawinska 8, 31-066 Cracow, Poland. E-mail: [email protected] | Institute of Mathematics, Warsaw University, Banacha 2, 02-097 Warszawa, Poland. E-mail: [email protected]

Abstract: The problem considered is how to model perception and identify behavioral patterns of objects changing over time in complex dynamical systems. An approach to solving this problem has been found in the context of rough set theory and methods. Rough set theory introduced by Zdzis?aw Pawlak during the early 1980s provides the foundation for the construction of classifiers, relative to what are known as temporal pattern tables. Temporal patterns can be treated as features that make it possible to approximate complex concepts. This article introduces some rough set tools for perception modeling that are developed for a system for modeling networks of classifiers. Such networks make it possible to identify behavioral patterns of objects changing over time. They are constructed using an ontology of concepts delivered by experts that engage in approximate reasoning about concepts embedded in such an ontology. We also present a method that we call a method for on-line elimination of non-relevant parts (ENP). This method was developed for on-line elimination of complex object parts that are irrelevant for identifying a given behavioral pattern. The article includes results of experiments that have been performed on data from a vehicular traffic simulator and on medical data obtained from Neonatal Intensive Care Unit in the Department of Pediatrics, Collegium Medicum, Jagiellonian University. The contribution of this article is the introduction of a network of classifiers that make it possible to identify the behavioral patterns of objects that change over time.

Keywords: behavioral pattern, rough sets, concept approximation, complex dynamical system, respiratory failure

Journal: Fundamenta Informaticae, vol. 75, no. 1-4, pp. 27-47, 2007