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Gaussian Membership Functions Are Most Adequate (1992)  (Make Corrections)  
In Representing Uncertainty In Measurements V. Kreinovich, C. Quintana, L....



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Abstract: In rare situations like fundamental physics we perform experiments without knowing what their results will be. In the majority of real-life measurement situations, we more or less know beforehand what kind of results we will get. Of course, this is not the precise knowledge of the type "the result will be between a \Gamma ffi and a + ffi", because in this case, we would not need any measurements at all. This is usually a knowledge that is best represented in uncertain terms, like "perhaps (or... (Update)

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BibTeX entry:   (Update)

@misc{ uncertainty-gaussian,
  author = "In Representing Uncertainty",
  title = "Gaussian Membership Functions Are Most Adequate",
  url = "citeseer.ist.psu.edu/660773.html" }
Citations (may not include all citations):
526   Information and control (context) - Zadeh - 1965
59   Lectures on functional equations and their applications (context) - Aczel - 1966
21   What non- linearity to choose (context) - Kreinovich, Quintana et al.
13   Statistics with vague data (context) - Kruse, Meyer - 1987
13   Integration of fuzzy logical information (context) - Oden - 1977
6   A fuzzy-set approach to modifiers and vagueness in natural l.. (context) - Hersch, Caramazza - 1976
6   Results of empirical studies in fuzzy set theory (context) - Zimmermann - 1978
6   Application of fuzzy reasoning to the water purification pro.. (context) - Yagishita, Itoh et al. - 1985
2   Methods and models of formalizing prior information (context) - Kreinovich, Reznik - 1986
1   Development of perfomance adaptive fuzzy controllers with ap.. (context) - Bartolini, Casalino et al. - 1985
1   Introduction to the theory of fuzzy subsets (context) - Kauffman - 1975

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