What is Fuzzy Inference System (FIS)

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The system which is a way of mapping an input space to an output space by using fuzzy set theory. FIS uses a collection of fuzzy membership functions and rules to generate an output. Learn more in: Fuzzy Logic Approach in Risk Assessment

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The system which is a way of mapping an input space to an output space by using fuzzy set theory. FIS uses a collection of fuzzy membership functions and rules to generate an output. Learn more in: Fuzzy Logic Approach in Risk Assessment

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The FIS is used for mapping the inputs to outputs by utilizing the fuzzy set theory. The inputs and outputs represent features and classes respectively with regards to fuzzy classification. Learn more in: Adaptive Neuro-Fuzzy Inference System in Agriculture

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A FIS is a way of mapping an input space to an output space using fuzzy logic. FIS uses a collection of fuzzy membership functions and rules, instead of Boolean logic, to reason about data. Learn more in: Biometric Identification System Using Neuro and Fuzzy Computational Approaches

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Fuzzy inference systems have been successfully applied in fields such as automatic control, data classification, decision analysis, expert systems, and computer vision. Because of its multidisciplinary nature, the fuzzy inference system is known by a number of names, such as fuzzy rule-based system. Learn more in: Automatic Detection of Tumor and Bleed in Magnetic Resonance Brain Images