Reduction of Neighborhood-Based Generalized Rough Sets
نویسندگان
چکیده
منابع مشابه
Reduction of Neighborhood-Based Generalized Rough Sets
Rough set theory is a powerful tool for dealing with uncertainty, granularity, and incompleteness of knowledge in information systems. This paper discusses five types of existing neighborhoodbased generalized rough sets. The concepts of minimal neighborhood description and maximal neighborhood description of an element are defined, and by means of the two concepts, the properties and structures...
متن کاملRough Entropy Based on Generalized Rough Sets Covering Reduction
In generalized rough set covering reduction theory, it is necessary to find a new measure to knowledge and rough set because the upper and lower approximations of rough sets are determined by their covering reduction. In this paper, information entropy is introduced to discuss the rough entropy of knowledge and the roughness of rough set, based on generalized rough set covering reduction. A new...
متن کاملReduction of Rough Set Based on Generalized Neighborhood System Operator
The theory of generalized neighborhood system-based approximation operators plays an important role in the theory of generalized rough sets since it includes both the neighborhood-based approximation operators and the covering-based approximation operators as its special circumstances. The theory of reduction is one of the most significant directions in rough sets. In this work, the reduction o...
متن کاملNew Neighborhood Based Rough Sets
Neighborhood based rough sets are important generalizations of the classical rough sets of Pawlak, as neighborhood operators generalize equivalence classes. In this article, we introduce nine neighborhood based operators and we study the partial order relations between twenty-two different neighborhood operators obtained from one covering. Seven neighborhood operators result in new rough set ap...
متن کاملHeterogeneous Attribute Reduction in Noisy System based on a Generalized Neighborhood Rough Sets Model
Neighborhood Rough Sets (NRS) has been proven to be an efficient tool for heterogeneous attribute reduction. However, most of researches are focused on dealing with complete and noiseless data. Factually, most of the information systems are noisy, namely, filled with incomplete data and inconsistent data. In this paper, we introduce a generalized neighborhood rough sets model, called VPTNRS, to...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Applied Mathematics
سال: 2011
ISSN: 1110-757X,1687-0042
DOI: 10.1155/2011/409181