Titlebook: Soft Methods for Integrated Uncertainty Modelling; Jonathan Lawry,Enrique Miranda,Olgierd Hyrniewicz Book 2006 Springer-Verlag Berlin Heid

排斥

Book 2006on and ig- rance present in a problem should be explicitly represented and possibly even - ploited rather than either eliminated or ignored in computations. For instance, Zadeh de?ned ‘Soft Computing’ as follows: Soft computing differs from conventional (hard) computing in that, unlike hard computin

HARP

1867-5662 ts in Soft Computing and Statistics.Includes supplementary mThe idea of soft computing emerged in the early 1990s from the fuzzy systems c- munity, and refers to an understanding that the uncertainty, imprecision and ig- rance present in a problem should be explicitly represented and possibly even -

Emmenagogue

Soft Methods in Earth Systems Engineeringsciously engages with society and the natural environment means that approaches based upon the strictures of individual decision rationality may have to be modified as part of collective and perhaps highly contested decision processes.

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Admire

影響

Statistical Data Processing under Interval Uncertainty: Algorithms and Computational Complexity. Specifically, we find some easier-to-measure quantities .,…,. which are related to . by a known relation . = . (.,…,.); this relation may be a simple functional transformation, or complex algorithm (e.g., for the amount of oil, numerical solution to an inverse problem).

CRUDE

Arthr-

An Asymptotic Test for Symmetry of Random Variables Based on Fuzzy Toolsies concerning the expected value of fuzzy random variables provide us with a tool to analyze the asymmetry degree from random samples. As a first step, we propose an asymptotic test of symmetry. We present some examples and simulations to illustrate the behaviour of the proposed test.

chastise

Fuzzy Probability Distributions Induced by Fuzzy Random Vectorshe probability of an event . can be regarded as the limit of the relative frequencies of . induced by a sequence of identically distributed, independent, integrable random variables (..). (with probability one).

Canopy

Exploratory Analysis of Random Variables Based on Fuzzificationsthe dispersion and the symmetry. The fuzzy representation is valuable for representing continuous or discrete distributions, thus, it can be employed both for representing population distributions and for exploratory data analysis.