Dominance-based rough set model in intuitionistic fuzzy information systems
Intuitionistic fuzzy information systems are generalized types of conventional fuzzy-valued information systems. By introducing a dominance relation to intuitionistic fuzzy information systems, we propose a notion of dominance intuitionistic fuzzy information systems (DIFIS) and establish a dominanc...
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Veröffentlicht in: | Knowledge-based systems 2012-04, Vol.28, p.115-123 |
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creator | Huang, Bing Li, Hua-xiong Wei, Da-kuan |
description | Intuitionistic fuzzy information systems are generalized types of conventional fuzzy-valued information systems. By introducing a dominance relation to intuitionistic fuzzy information systems, we propose a notion of dominance intuitionistic fuzzy information systems (DIFIS) and establish a dominance-based rough set model, which is mainly based on the substitution of the indiscernibility relation in classic rough set theory by a dominance relation that is defined on the score and accuracy function of intuitionistic fuzzy value in DIFIS. Furthermore, to simplify the knowledge representation and extract useful and simpler dominance intuitionistic fuzzy rules, we provide two attribute reduction approaches to eliminate the redundant information. Finally, we apply these approaches to computer auditing risk assessment, and by using an application as a case study we acquire some valuable assessment rules. These resulting rules can provide an available method to acquire knowledge from DIFISs. |
doi_str_mv | 10.1016/j.knosys.2011.12.008 |
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By introducing a dominance relation to intuitionistic fuzzy information systems, we propose a notion of dominance intuitionistic fuzzy information systems (DIFIS) and establish a dominance-based rough set model, which is mainly based on the substitution of the indiscernibility relation in classic rough set theory by a dominance relation that is defined on the score and accuracy function of intuitionistic fuzzy value in DIFIS. Furthermore, to simplify the knowledge representation and extract useful and simpler dominance intuitionistic fuzzy rules, we provide two attribute reduction approaches to eliminate the redundant information. Finally, we apply these approaches to computer auditing risk assessment, and by using an application as a case study we acquire some valuable assessment rules. 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By introducing a dominance relation to intuitionistic fuzzy information systems, we propose a notion of dominance intuitionistic fuzzy information systems (DIFIS) and establish a dominance-based rough set model, which is mainly based on the substitution of the indiscernibility relation in classic rough set theory by a dominance relation that is defined on the score and accuracy function of intuitionistic fuzzy value in DIFIS. Furthermore, to simplify the knowledge representation and extract useful and simpler dominance intuitionistic fuzzy rules, we provide two attribute reduction approaches to eliminate the redundant information. Finally, we apply these approaches to computer auditing risk assessment, and by using an application as a case study we acquire some valuable assessment rules. These resulting rules can provide an available method to acquire knowledge from DIFISs.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.knosys.2011.12.008</doi><tpages>9</tpages></addata></record> |
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subjects | DIFIS Discernibility matrix Dominance relation Reduction Rough set model |
title | Dominance-based rough set model in intuitionistic fuzzy information systems |
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