Measurement Of Uncertainty In Several Different Types Of Information Systems

Uncertainty,including randomness,fuzziness,vagueness,incompleteness and inconsistency,nearly exists in everywhere of the real world.The measurement uncertainty of rough sets is a hot research topic in recent years.Moreover,based on rough set theory,an information system as a database that represents relationships between objects and attributes.An information system is an important part of artificial intelligence.At present,granular computing is one of significant tools in artificial intelligence.This dissertation mainly studies uncertainty measurement of three different types of information systems.And the correlation and dispersion between them are discussed through numerical experiments and effectiveness analysis.In chapter 2,the uncertainty measurement for a covering information system is studied.A covering information system is introduced that induced by an incomplete information system.Four measurement tools as well as related algorithm in a covering information system are proposed.In chapter 3,the uncertainty measurement for a hybrid information system with images is researched.The distance between two information function values based on the attribute set in a hybrid information system with images is explored.The tolerance relation on an object set,induced by a hybrid information system with images by using this distance,is obtained.Moreover,information structures and uncertainty measurement of in a hybrid information system with images are proposed.In chapter 4,the uncertainty measurement for a fuzzy relation information system is investigated.A fuzzy relation information system may be viewed as a universe with multiple fuzzy relations.The concept of upper and lower information structures in a fuzzy relation information system is described by using set vectors.The uncertainty measurement in a fuzzy relation information system and the characterizations under a compatible homomorphism are proposed.