The concept of the rough set was originally proposed by Pawlak as a formal tool for modelling and processing incomplete information in information systems, then in 1990, Dubois and Prade first introduced the rough fuzzy sets and fuzzy rough sets as a fuzzy extension of the rough sets. The aim of this paper is to present a new extension of the rough set theory by means of integrating the classic...

seismic hazard assessment like many other issues in seismology is a complicated problem, which is due to variety of parameters affecting the occurrence of earthquake. uncertainty, which is a result of vagueness and incompleteness of the data, should be considered in a rationale way. herein, fuzzy set theory is used to take into account the uncertainty existed in the seismic hazard analysis. the...

A concept of fuzzy discretization of feature space for a rough set theoretic classifier is explained. Fuzzy discretization is characterised by membership value, group number and affinity corresponding to an attribute value, unlike crisp discretization which is characterised only by the group number. The merit of this approach over both crisp discretization in terms of classification accuracy, i...

This issue introduces the state-of-art in granular soft computng for pattern recognition and mining and presents some novel ontributions. Granulation is a computing paradigm, among othrs such as self-reproduction, self-organization, functioning of rain, Darwinian evolution, group behavior, cell membranes, and orphogenesis that are abstracted from natural phenomena. Granlation is inherent in hum...

In this paper, we propose a dominance-based rough set approach for the decision analysis of a preference-ordered uncertain data table, which is comprised of a finite set of objects described by a finite set of criteria. The domains of the criteria may have ordinal properties that express preference scales. In the proposed approach, we first compute the degree of dominance between any two object...

Natural computing, inspired by biological course of action, is an interdisciplinary field that formalizes processes observed in living organisms to design computational methods for solving complex problems, or designing artificial systems with more natural behaviour. Based on the tasks abstracted from natural phenomena, such as brain modelling, self-organization, self-repetition, self evaluatio...

Fuzzy covering-based rough set models are hybrid models using both rough set and fuzzy set theory. The former is often used to deal with uncertain and incomplete information, while the latter is used to describe vague concepts. The study of fuzzy rough set models has provided very good tools for machine learning algorithms such as feature and instance selection. In this article, we discuss diff...

The lower and upper approximations are basic concepts in rough set theory, and the approximations will change dynamically over time. Incremental methods for updating approximations in rough set theory and its extension has been received much attention recently. This paper presents an approach for incrementally updating approximations of fuzzy rough sets in dynamic fuzzy decision systems when a ...

The notion of three-way decisions was originally introduced by the needs to explain the three regions of probabilistic rough sets. Recent studies show that rough set theory is only one of possible ways to construct three regions. A more general theory of three-way decisions has been proposed, embracing ideas from rough sets, interval sets, shadowed sets, three-way approximations of fuzzy sets, ...