Results 261 to 270 of about 58,797 (306)
Some of the next articles are maybe not open access.
Information Sciences, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zdzisław Pawlak, Andrzej Skowron
exaly +3 more sources
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zdzisław Pawlak, Andrzej Skowron
exaly +3 more sources
ROUGH FUZZY SETS AND FUZZY ROUGH SETS*
International Journal of General Systems, 1990The notion of a rough set introduced by Pawlak has often been compared to that of a fuzzy set, sometimes with a view to prove that one is more general, or, more useful than the other. In this paper we argue that both notions aim to different purposes.
Henri Prade
exaly +3 more sources
Information Sciences, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Feng Feng, Young Bae Jun
exaly +2 more sources
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Feng Feng, Young Bae Jun
exaly +2 more sources
Communications of the ACM, 1995
Rough set theory, introduced by Zdzislaw Pawlak in the early 1980s [11, 12], is a new mathematical tool to deal with vagueness and uncertainty. This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge ...
Zdzislaw Pawlak +3 more
openaire +1 more source
Rough set theory, introduced by Zdzislaw Pawlak in the early 1980s [11, 12], is a new mathematical tool to deal with vagueness and uncertainty. This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge ...
Zdzislaw Pawlak +3 more
openaire +1 more source
2015
As quantitative generalizations of Pawlak rough sets, probabilistic rough sets consider degrees of overlap between equivalence classes and the set. An equivalence class is put into the lower approximation if the conditional probability of the set, given the equivalence class, is equal to or above one threshold; an equivalence class is put into the ...
Yao, Yiyu +2 more
openaire +1 more source
As quantitative generalizations of Pawlak rough sets, probabilistic rough sets consider degrees of overlap between equivalence classes and the set. An equivalence class is put into the lower approximation if the conditional probability of the set, given the equivalence class, is equal to or above one threshold; an equivalence class is put into the ...
Yao, Yiyu +2 more
openaire +1 more source
Information Sciences
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Qingzhao Kong, Conghao Yan, Weihua Xu
openaire +2 more sources
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Qingzhao Kong, Conghao Yan, Weihua Xu
openaire +2 more sources
2004
We study the ordered set of rough sets determined by relations which are not necessarily reflexive, symmetric, or transitive. We show that for tolerances and transitive binary relations the set of rough sets is not necessarily even a semilattice. We also prove that the set of rough sets determined by a symmetric and transitive binary relation forms a ...
openaire +1 more source
We study the ordered set of rough sets determined by relations which are not necessarily reflexive, symmetric, or transitive. We show that for tolerances and transitive binary relations the set of rough sets is not necessarily even a semilattice. We also prove that the set of rough sets determined by a symmetric and transitive binary relation forms a ...
openaire +1 more source
1994
It is shown that the modal system S5 captures the basic propositional aspects of rough set theory. The system S5 is enhanced to define a consequence relation called ‘rough consequence’ to ensure derivability of ‘roughly equal’ formulae. A predicate logic that includes in its ambit all the existing notions of rough set theory, is presented.
Mohua Banerjee, Mihir K. Chakraborty
openaire +1 more source
It is shown that the modal system S5 captures the basic propositional aspects of rough set theory. The system S5 is enhanced to define a consequence relation called ‘rough consequence’ to ensure derivability of ‘roughly equal’ formulae. A predicate logic that includes in its ambit all the existing notions of rough set theory, is presented.
Mohua Banerjee, Mihir K. Chakraborty
openaire +1 more source
2015
This chapter reviews three formulations of rough set theory, i. e., element-based definition, granule-based definition, and subsystem-based definition. These formulations are adopted to generalize rough sets from three directions. The first direction is to use an arbitrary binary relation to generalize the equivalence relation in the element-based ...
Yao, J, CIUCCI, DAVIDE ELIO, Zhang, Y.
openaire +2 more sources
This chapter reviews three formulations of rough set theory, i. e., element-based definition, granule-based definition, and subsystem-based definition. These formulations are adopted to generalize rough sets from three directions. The first direction is to use an arbitrary binary relation to generalize the equivalence relation in the element-based ...
Yao, J, CIUCCI, DAVIDE ELIO, Zhang, Y.
openaire +2 more sources