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2017 | OriginalPaper | Chapter

Fuzzy Uncertainty in Random Variable Generation: A Cumulative Membership Function Approach

Authors : Diana Giseth Pulido-López, Mabel García, Juan Carlos Figueroa-García

Published in: Applied Computer Sciences in Engineering

Publisher: Springer International Publishing

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Abstract

This paper presents a method for random variable generation based on the cumulative membership function. The proposed method uses fuzzy numbers and uniformly distributed random numbers to obtain a random variable, mainly used in simulation models.

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previous chapter Classification by Nearest Neighbor and Multilayer Perceptron a New Approach Based on Fuzzy Similarity Quality Measure: A Case Study
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Footnotes
1
This expression denotes a fuzzy measurement of an event occurs treated as the Possibility (Ps).
 
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Figueroa-García, J.C., López-Bello, C.A.: Linear programming with fuzzy joint parameters: a cumulative membership function approach. In: Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS), pp. 1–6 (2008)
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Figueroa-García, J.C., López-Bello, C.A.: Pseudo-optimal solutions of FLP problems by using the cumulative membership function. In: Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS), vol. 28, pp. 1–6 (2009)
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Figueroa-García, J.C., Hernández-Pérez, G.J.: On the computation of the distance between interval type-2 fuzzy numbers using \(\alpha \)-cuts. In: Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS), pp. 1–6 (2014)
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Metadata
Title
Fuzzy Uncertainty in Random Variable Generation: A Cumulative Membership Function Approach
Authors
Diana Giseth Pulido-López
Mabel García
Juan Carlos Figueroa-García
Copyright Year
2017
Book
Applied Computer Sciences in Engineering

Print ISBN: 978-3-319-66962-5

Electronic ISBN: 978-3-319-66963-2

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-66963-2_36

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