Dominance-based rough set approach(DRSA) permits representation and analysis of all phenomena involving monotonicity relationship between some measures or perceptions.DRSA has also some merits within granular computin...Dominance-based rough set approach(DRSA) permits representation and analysis of all phenomena involving monotonicity relationship between some measures or perceptions.DRSA has also some merits within granular computing,as it extends the paradigm of granular computing to ordered data,specifies a syntax and modality of information granules which are appropriate for dealing with ordered data,and enables computing with words and reasoning about ordered data.Granular computing with ordered data is a very general paradigm,because other modalities of information constraints,such as veristic,possibilistic and probabilistic modalities,have also to deal with ordered value sets(with qualifiers relative to grades of truth,possibility and probability),which gives DRSA a large area of applications.展开更多
In order to understand the security conditions of the incomplete interval-valued information system （IllS） and acquire the corresponding solution of security problems, this paper proposes a multi-attribute group dec...In order to understand the security conditions of the incomplete interval-valued information system （IllS） and acquire the corresponding solution of security problems, this paper proposes a multi-attribute group decision- making （MAGDM） security assessment method based on the technique for order performance by similarity to ideal solution （TOPSIS）. For IllS with preference information, combining with dominance-based rough set approach （DRSA）, the effect of incomplete interval-valued information on decision results is discussed. For the imprecise judgment matrices, the security attribute weight can be obtained using Gibbs sampling. A numerical example shows that the proposed method can acquire some valuable knowledge hidden in the incomplete interval-valued information. The effectiveness of the proposed method in the synthetic security assessment for IIIS is verified.展开更多
文摘Dominance-based rough set approach(DRSA) permits representation and analysis of all phenomena involving monotonicity relationship between some measures or perceptions.DRSA has also some merits within granular computing,as it extends the paradigm of granular computing to ordered data,specifies a syntax and modality of information granules which are appropriate for dealing with ordered data,and enables computing with words and reasoning about ordered data.Granular computing with ordered data is a very general paradigm,because other modalities of information constraints,such as veristic,possibilistic and probabilistic modalities,have also to deal with ordered value sets(with qualifiers relative to grades of truth,possibility and probability),which gives DRSA a large area of applications.
基金Supported by the National Natural Science Foundation of China（No.60605019）
文摘In order to understand the security conditions of the incomplete interval-valued information system （IllS） and acquire the corresponding solution of security problems, this paper proposes a multi-attribute group decision- making （MAGDM） security assessment method based on the technique for order performance by similarity to ideal solution （TOPSIS）. For IllS with preference information, combining with dominance-based rough set approach （DRSA）, the effect of incomplete interval-valued information on decision results is discussed. For the imprecise judgment matrices, the security attribute weight can be obtained using Gibbs sampling. A numerical example shows that the proposed method can acquire some valuable knowledge hidden in the incomplete interval-valued information. The effectiveness of the proposed method in the synthetic security assessment for IIIS is verified.
