Abstract. Rough sets have traditionally been applied to decision (classification) problems. We suggest that rough sets are even better suited for reasoning. It has already been sho...
We discuss how Case Based Reasoning (CBR) (see e.g. [1], [4]) philosophy of adaptation of some known situations to new similar ones can be realized in rough set framework [5] for c...
The aim of the paper is to present basic notions related to granular computing, namely the information granule syntax and semantics as well as the inclusion and closeness (similari...
Andrzej Skowron, Jaroslaw Stepaniuk, James F. Pete...
In the paper we investigate the problem of analysis of time related information systems. We introduce notion of temporal templates, i.e. homogeneous patterns occurring in some peri...
In this paper we introduce the concept of valued tolerance as an extension of the usual concept of indiscernibility (which is a crisp equivalence relation) in rough sets theory. So...
The optimization of rough set based classification models with respect to parameterized balance between a model's complexity and confidence is discussed. For this purpose, the...
This paper introduces a neural network architecture based on rough sets and rough membership functions. The neurons of such networks instantiate approximate reasoning in assessing ...
James F. Peters, Andrzej Skowron, Liting Han, Shee...
Abstract. An approach to a multi-facet task of situation identification by Unmanned Aerial Vehicle (UAV) is presented. The concept of multi-layered identification system based on s...
Hung Son Nguyen, Andrzej Skowron, Marcin S. Szczuk...
The main task in decision tree construction algorithms is to find the "best partition" of the set of objects. In this paper, we investigate the problem of optimal binary ...