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Published in Philip A. Laplante, Comprehensive Dictionary of Electrical Engineering, 2018
fuzzy integral an aggregation operator used to integrate multiattribute fuzzy information. It is a functional defined by using fuzzy measures, which corresponds to probability expectations. Two commonly used fuzzy integrals are Sugeno integral and Choquet integral. fuzzy intensification an operator that increases the membership function of a fuzzy set above the crossover point and decreases that of a fuzzy set below the crossover point. fuzzy intersection the fuzzy intersection is interpreted as "A AND B," which takes the minimum value of the two membership functions. fuzzy ISODATA See fuzzy c-means.
F
Published in Phillip A. Laplante, Dictionary of Computer Science, Engineering, and Technology, 2017
fuzzy integral an aggregation operator used to integrate multi-attribute fuzzy information. It is a functional defined by using fuzzy measures, which corresponds to probability expectations. Two commonly used fuzzy integrals are Sugeno integral and Choquet integral.
Using preference leveled evaluation functions to construct fuzzy measures in decision making and evaluation
Published in International Journal of General Systems, 2020
Chen Zhu, LeSheng Jin, Radko Mesiar, Ronald R. Yager
may be replaced by other t-conorms (Klement, Mesiar, and Pap 2000). Recall also that the aforementioned aggregation function G is also called the expected value of a fuzzy set (Grabisch et al. 2009). As in a special situation where a fuzzy measure is given, for the possible selections about aggregation function G, one may also chooses to use the fuzzy measure based aggregation functions such as Choquet Integral (Choquet 1954) or Sugeno Integral (Sugeno 1974).
Generalizing expected values to the case of L *-fuzzy events
Published in International Journal of General Systems, 2021
Erich Peter Klement, Fateme Kouchakinejad, Debashree Guha, Radko Mesiar
This procedure can be further generalized by considering more general types of measures (such as capacities (Choquet 1954) or fuzzy measures (Sugeno 1974)) and more general types of integrals (such as the Choquet (Choquet 1954), Shilkret (Shilkret 1971) or Sugeno integral (Sugeno 1974), or even a more abstract framework for integrals such as the universal integrals studied in Klement, Mesiar, and Pap (2010)) to define expected values of fuzzy events (Klement and Mesiar 2015).