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

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Applied Computer Sciences in Engineering (WEA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 742))

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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.

D.G. Pulido-López—Undergraduate student at the Universidad Distrital Francisco José de Caldas, Bogotá - Colombia.

M. García—Undergraduate student at the Universidad Distrital Francisco José de Caldas, Bogotá - Colombia.

J.C. Figueroa-García—Assistant Professor at the Universidad Distrital Francisco José de Caldas, Bogotá - Colombia.

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Notes

  1. 1.

    This expression denotes a fuzzy measurement of an event occurs treated as the Possibility (Ps).

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Correspondence to Juan Carlos Figueroa-García .

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Pulido-López, D.G., García, M., Figueroa-García, J.C. (2017). Fuzzy Uncertainty in Random Variable Generation: A Cumulative Membership Function Approach. In: Figueroa-García, J., López-Santana, E., Villa-Ramírez, J., Ferro-Escobar, R. (eds) Applied Computer Sciences in Engineering. WEA 2017. Communications in Computer and Information Science, vol 742. Springer, Cham. https://doi.org/10.1007/978-3-319-66963-2_36

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

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