Results 241 to 250 of about 24,695,904 (268)

Dominance-Based Rough Set Approach as a Proper Way of Handling Graduality in Rough Set Theory

2007
Referring to some ideas of Leibniz, Frege, Boole and Łukasie-wicz, we represent fundamental concepts of rough set theory in terms of a generalization that permits to deal with the graduality of fuzzy sets. Our conjunction of rough sets and fuzzy sets is made using the Dominance-based Rough Set Approach (DRSA).
GRECO S, MATARAZZO B., SLOWINSKI R
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Dominance Based Rough Set APIs Library

2019
In this chapter we will present VBA source code for calculating approximations. We will calculate both lower and upper approximations along with dominance relation and class unions. The main intention of the chapter is to clear the programming logic behind calculating these measures. At this point it is referred to have some basic tutorial about VBA.
Muhammad Summair Raza, Usman Qamar
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Dominance-Based Neighborhood Rough Sets and Its Attribute Reduction

2015
In real-life applications, partial order may exist in the domain of attributes and different data types often coexist in an decision system. Dominance-based rough set approach has been used widely in multi-attribute and multi-criteria decision by using the dominating relation. Neighborhood rough set aims to deal with hybrid data types.
Hongmei Chen 0001, Tianrui Li 0001, Chuan Luo 0001, Jie Hu 0007   +3 more
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Dominance-Based Rough Set Approach for Decision Analysis - A Tutorial

2008
Scientific analysis of decision problems aims at giving the decision maker (DM) a recommendation concerning a set of objects (called also alternatives, solutions, acts, actions, cases, candidates) evaluated wiht respect to a plurality of their characteristics considered relevant for the problem at hand, and called attributes.
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Optimized Generalized Decision in Dominance-Based Rough Set Approach

2007
Dominance-based Rough Set Approach (DRSA) has been proposed to deal with multi-criteria classification problems, where data may be inconsistent with respect to the dominance principle. However, in real-life datasets, in the presence of noise, the notions of lower and upper approximations handling inconsistencies were found to be excessively restrictive
Krzysztof Dembczynski, Salvatore Greco, Wojciech Kotlowski, Roman Slowinski   +3 more
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Dominance-Based Rough Set Approach for Possibilistic Information Systems

2011
In this paper, we propose a dominance-based fuzzy rough set approach for the decision analysis of a preference-ordered possibilistic information systems, 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.
Tuan-Fang Fan, Churn-Jung Liau, Duen-Ren Liu   +2 more
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Bayesian Decision Theory for Dominance-Based Rough Set Approach

2007
Dominance-based Rough Set Approach (DRSA) has been proposed to generalize classical rough set approach when consideration of monotonicity between degrees of membership to considered concepts has to be taken into account. This is typical for data describing various phenomena, e.g., "the larger the mass and the smaller the distance, the larger the ...
GRECO, Salvatore, SLOWINSKI R, AND YAO Y.   +2 more
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Redefining preliminaries of dominance-based rough set approach

Soft Computing, 2022
Faryal Nosheen, Usman Qamar, Muhammad Summair Raza   +2 more
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A Comprehensive Study on Reducts in Dominance-Based Rough Set Approach

2008
In this paper, we propose new reducts in the dominance-based rough set approach. The relations with previous ones are clarified. Moreover, a comprehensive enumeration method of all kinds of reducts is proposed. We show that all kinds of reducts are enumerated based on two discernibility matrices associated with generalized decisions.
Yoshifumi Kusunoki, Masahiro Inuiguchi
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Approximate dominance-based rough sets using equivalence granules

2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence), 2008
The rough set theory introduced by Pawlak has provided a solid foundation for developing many useful learning algorithms and tools for data analysis. Dominance-based rough set introduced by Greco et al. is an extension of classical rough sets for dealing with multiple criteria decision analysis problems.
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