Results 261 to 270 of about 6,770,857 (301)

Convergence of sequence of measurable functions on fuzzy measure spaces

Fuzzy Sets and Systems, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jun Li 0014, Masami Yasuda, Qingshan Jiang, Hisakichi Suzuki, Zhenyuan Wang, George J. Klir   +5 more
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Measures of compactness in L-fuzzy pretopological spaces

Journal of Intelligent & Fuzzy Systems, 2014
In this paper, we introduce the concepts of the degrees of compactness, countable compactness and Lindelöf property in L-fuzzy pretopological spaces by means of implication operator. These definitions do not rely on the structure of the basis lattice L and no distributivity in L is required.
Fu-Gui Shi, Chengyu Liang
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Measurable Functions on Fuzzy Measure Spaces

1992
In this chapter, let (X, ℱ) be a measurable space, μ: F → [0, ∞] be a fuzzy measure (or semicontinuous fuzzy measure), and B be the Borel field on (−∞, ∞).
Zhenyuan Wang, George J. Klir
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A further investigation for fuzzy measures on metric spaces

Fuzzy Sets and Systems, 1999
A set function \(m: B\to [0,\infty]\) defined on the family of all Borel subsets of a metric space is an LSC-fuzzy measure if \(m(\emptyset)=0\), \(m\) is monotone and continuous from below. It is said to be exhaustive if \(\lim m(E_n)= 0\) for any disjoint sequence \((E_n)\).
Qingshan Jiang, Shengrui Wang, Djemel Ziou   +2 more
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Probability measures over fuzzy spaces

International Journal of General Systems, 2007
A probability measure is defined on subsets of an underlying space. In classical probability theory, both the underlying space and the subsets whose probabilities we measure are crisp subsets. Zadeh provided an extension of this to the case in which the subsets whose probabilities we are measuring can be fuzzy. Here, we provide a further generalization
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On Egoroff's theorems on fuzzy measure spaces

Fuzzy Sets and Systems, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Notes on Riesz's theorem on fuzzy measure space

Fuzzy Sets and Systems, 1997
A fuzzy measure is considered as a non-negative function, zero in the empty set, monotone and continuous. A necessary and sufficient condition is given for every sequence of non-negative finite measurable functions converging in measure to contain a subsequence converging a.e.
Minghu Ha 0001, Lixin Cheng, Xizhao Wang
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The fuzzy integral on product spaces for NSA measures

Fuzzy Sets and Systems, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
E. Suárez Díaz, F. Suárez García
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Fundamental convergence of sequences of measurable functions on fuzzy measure space

Fuzzy Sets and Systems, 1998
A fuzzy measure is considered as a monotone, continuous (from above and from below) extended real-valued function \(m\) defined on a \(\sigma\)-algebra such that \(m(\emptyset)=0\). It is said to be asymptotically null-additive, if \(m(A_n\cup B_m) \to 0\) \((n\to \infty,\;m\to \infty)\) whenever \(m(A_n) \to 0\) and \(m(B_m)\to 0\).
Minghu Ha 0001, Xizhao Wang, Congxin Wu
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On the extension of the fuzzy number measures in Banach spaces: Part I. Representation of the fuzzy number measures

Fuzzy Sets and Systems, 1996
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Xiaoping Xue 0001, Minghu Ha 0001, Congxin Wu   +2 more
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