Results 231 to 240 of about 4,333 (278)

A Semantical Approach to Rough Sets and Dominance-Based Rough Sets

2016
There exist two formulations of rough sets: the conceptual and computational one. The conceptual or semantical approach of rough set theory focuses on the meaning and interpretation of concepts, while algorithms to compute those concepts are studied in the computational formulation. However, the research on the former is rather limited.
Lynn D’eer, Chris Cornelis, Yiyu Yao
openaire   +1 more source

Dominance-Based Rough Set Approach and Bipolar Abstract Rough Approximation Spaces

2008
We take into consideration Dominance-based Rough Set Approach and its recently proposed algebraic modeling in terms of bipolar de Morgan Brower-Zadeh distributive lattice. On this basis we introduce the concept of bipolar approximation space and we show how it can be induced from a bipolar quasi Brower-Zadeh lattice.
Greco, Salvatore, Matarazzo, Benedetto, Słowiński, Roman   +2 more
openaire   +2 more sources

Double-quantitative variable consistency dominance-based rough set approach

International Journal of Approximate Reasoning, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Li, Wentao, Xue, Xiaoping, Xu, Weihua, Zhan, Tao, Fan, Bingjiao   +4 more
openaire   +1 more source

Dominance-Based Rough Set Approach to Case-Based Reasoning

2006
Case-based reasoning is a paradigm in machine learning whose idea is that a new problem can be solved by noticing its similarity to a set of problems previously solved. We propose a new approach to case-based reasoning. It is based on rough set theory that is a mathematical theory for reasoning about data. More precisely, we adopt Dominance-based Rough
GRECO, Salvatore, MATARAZZO B, SLOWINSKI R.   +2 more
openaire   +3 more sources

Dominance-Based Rough Set Approach to Granular Computing

2010
Dominance-based Rough Set Approach (DRSA) was introduced as a generalization of the rough set approach for reasoning about preferences. While data describing preferences are ordinal by the nature of decision problems they concern, the ordering of data is also important in many other problems of data analysis.
GRECO, Salvatore, MATARAZZO B, SLOWINSKI R.   +2 more
openaire   +2 more sources

Dominance-Based Rough Set Approach Using Possibility and Necessity Measures

2002
Dominance-based rough set approach is an extension of the basic rough set approach proposed by Pawlak, to multicriteria classification problems. In this paper, the dominance-based rough set approach is considered in the context of vague information on preferences and decision classes.
GRECO, Salvatore, INUIGUCHI M, SLOWINSKI R.   +2 more
openaire   +3 more sources

Several Reducts in Dominance-Based Rough Set Approach

2008
In this paper, we investigate reducts preserving a structure induced from dominance-based rough sets as well as a structure from variable-precision dominance-based rough sets. It is shown that three kinds of reducts are obtained in the dominance-based rough set approach.
Masahiro Inuiguchi, Yukihiro Yoshioka
openaire   +1 more source

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
openaire   +3 more sources

A unified approach to reducts in dominance-based rough set approach

Soft Computing, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kusunoki, Yoshifumi, Inuiguchi, Masahiro
openaire   +1 more source

Dominance-Based Rough Set Approach to Interactive Evolutionary Multiobjective Optimization

2010
We present application of Dominance-based Rough Set Approach (DRSA) to interactive Evolutionary Multiobjective Optimization (EMO). In the proposed methodology, the preference information elicited by the decision maker in successive iterations consists in sorting some solutions of the current population as “good” or “bad”, or in comparing some pairs of ...
GRECO, Salvatore, MATARAZZO B, SLOWINSKI R.   +2 more
openaire   +2 more sources