Overview of Type-2 Fuzzy Logic Systems

摘要: Fuzzy set theory has been proposed as a means for modeling the vagueness in complex systems. systems usually employ type-1 fuzzy sets, representing uncertainty by numbers range [0, 1]. Despite commercial success of logic, T1FS does not capture its manifestations when it arises from shape membership function. Such uncertainties need to be depicted sets that have blur boundaries. The imprecise boundaries type-2 T2FS give rise truth/membership values are [0], [1], instead crisp number. Type-2 logic T2FLSs offer opportunity model levels which traditional type1 struggles. This extra dimension gives more degrees freedom better representation compared sets. A system T1FLSs inference produces and result defuzzification T1FS, number, whereas T2FLS set, type-reduced is set. output decision-making flexibilities. Thus, FLSs using provide capability handling higher level number missing components held back successful deployment decision making.