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000825564 0247_ $$a10.1007/978-3-319-72691-5$$2doi
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000825564 1001_ $$aAkama, Seiki,$$eauthor.
000825564 24510 $$aReasoning with rough sets :$$blogical approaches to granularity-based framework /$$cSeiki Akama, Tetsuya Murai, Yasuo Kudo.
000825564 260__ $$aCham :$$bSpringer,$$c2018.
000825564 300__ $$a1 online resource.
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000825564 4901_ $$aIntelligent systems reference library ;$$vvolume 142
000825564 506__ $$aAccess limited to authorized users.
000825564 520__ $$aThis book explores reasoning with rough sets by developing a granularity-based framework. It begins with a brief description of rough set theory. Next, we examine some relations between rough set theory and non-classical logics including modal logic. We also develop a granularity-based framework for reasoning in which various types of reasoning can be formalized. This book will be of interest to researchers working on the areas in Artificial Intelligence, database and logic.
000825564 588__ $$aOnline resource; title from PDF title page (viewed January 11, 2018).
000825564 650_0 $$aRough sets.
000825564 650_0 $$aGranular computing.
000825564 650_0 $$aData mining.
000825564 7001_ $$aMurai, Tetsuya,$$eauthor.
000825564 7001_ $$aKudo, Yasuo,$$eauthor.
000825564 77608 $$iPrint version:$$aAkama, Seiki.$$tReasoning with rough sets.$$dCham : Springer, 2018$$z3319726900$$z9783319726908$$w(OCoLC)1012273899
000825564 830_0 $$aIntelligent systems reference library ;$$vv. 142.
000825564 852__ $$bebk
000825564 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-72691-5$$zOnline Access$$91397441.1
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