Stratified Rough Sets and Vagueness

نویسندگان

  • Thomas Bittner
  • John G. Stell
چکیده

The relationship between less detailed and more detailed versions of data is one of the major issues in processing geographic information. Fundamental to much work in model-oriented generalization, also called semantic generalization, is the notion of an equivalence relation. Given an equivalence relation on a set, the techniques of rough set theory can be applied to give generalized descriptions of subsets of the original set. The notion of equivalence relation, or partition, has recently been significantly extended by the introduction of the notion of a granular partition. A granular partition provides what may be thought of as a hierarchical family of partial equivalence relations. In this paper we show how the mechanisms for making rough descriptions with respect to an equivalence relation can be extended to give rough descriptions with respect to a granular partition. In order to do this, we also show how some of the theory of granular partitions can be reformulated; this clarifies the connections between equivalence relations and granular partitions. With the help of this correspondence we then can show how the notion of hierarchical systems of partial equivalence classes relates to partitions of partial sets, i.e., partitions of sets in which not all members are known. This gives us new insight into the relationships between roughness and vagueness.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Rough sets theory in site selection decision making for water reservoirs

Rough Sets theory is a mathematical approach for analysis of a vague description of objects presented by a well-known mathematician, Pawlak (1982, 1991). This paper explores the use of Rough Sets theory in site location investigation of buried concrete water reservoirs. Making an appropriate decision in site location can always avoid unnecessary expensive costs which is very important in constr...

متن کامل

Structure of Covering-based Rough Sets

Rough set theory is a very effective tool to deal with granularity and vagueness in information systems. Covering-based rough set theory is an extension of classical rough set theory. In this paper, firstly we present the characteristics of the reducible element and the minimal description covering-based rough sets through downsets. Then we establish lattices and topological spaces in coveringb...

متن کامل

Fuzzy Rough Sets and Its Application in Data Mining Field

Rough set theory is a new method that deals with vagueness and uncertainty emphasized in decision making. The theory provides a practical approach for extraction of valid rules fromdata.This paper discusses about rough sets and fuzzy rough sets with its applications in data mining that can handle uncertain and vague data so as to reach at meaningful conclusions.

متن کامل

Another approach to soft rough sets

Theories of soft sets and rough sets are two different approaches to vagueness. A possible fusion of rough sets and soft sets is proposed by F.Feng et al. They introduce the concept of soft rough sets, where parametrized subsets of a universe set are basic building blocks for lower and upper approximations of a subset. In the present paper, a new approach is being introduced to study roughness ...

متن کامل

Rough Mereology in Analysis of Vagueness

This work aims at presenting to a wider audience fundamental notions and ideas of rough mereology. We discuss various methods for constructing rough inclusions in data sets, then we show how to apply them to the task of knowledge granulation, and finally, we introduce granular reflections of data sets with examples of classifiers built on them.

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2003