Random variate generation for discrete fuzzy numbers based on α-cuts

Juan Carlos Figueroa-García; Carlos Franco; Roman Neruda

doi:10.1109/BDAI62182.2024.10692377

Random variate generation for discrete fuzzy numbers based on α-cuts

Juan Carlos Figueroa-García, Carlos Franco, Roman Neruda

School of Business Administration

Research output: Chapter in Book/Inform › Conference contribution

Abstract

Probabilistic based random variate generation is the most popular method for representing randomness into simulation scenarios that could occur in real life. The main idea behind the use of random numbers to replicate the value of a uncertain variable can also be extended to fuzzy sets, including discrete fuzzy sets. This way, it is possible to use random numbers and the α -cut of a discrete fuzzy set to retrieve a random variate alongside its membership degree. To do so, a method for computing discrete fuzzy random variates based on α -cuts is proposed and applied to two examples: a comprehensive and a simulation example.

Original language	English (US)
Title of host publication	2024 IEEE 7th International Conference on Big Data and Artificial Intelligence, BDAI 2024
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	259-264
Number of pages	6
ISBN (Electronic)	9798350352009
DOIs	https://doi.org/10.1109/BDAI62182.2024.10692377
State	Published - 2024
Event	7th IEEE International Conference on Big Data and Artificial Intelligence, BDAI 2024 - Beijing, China Duration: Jul 5 2024 → Jul 7 2024

Publication series

Name	2024 IEEE 7th International Conference on Big Data and Artificial Intelligence, BDAI 2024

Conference

Conference	7th IEEE International Conference on Big Data and Artificial Intelligence, BDAI 2024
Country/Territory	China
City	Beijing
Period	7/5/24 → 7/7/24

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Computer Vision and Pattern Recognition
Information Systems
Information Systems and Management

Access to Document

10.1109/BDAI62182.2024.10692377

Cite this

Figueroa-García, J. C., Franco, C., & Neruda, R. (2024). Random variate generation for discrete fuzzy numbers based on α-cuts. In 2024 IEEE 7th International Conference on Big Data and Artificial Intelligence, BDAI 2024 (pp. 259-264). (2024 IEEE 7th International Conference on Big Data and Artificial Intelligence, BDAI 2024). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BDAI62182.2024.10692377

Figueroa-García, Juan Carlos ; Franco, Carlos ; Neruda, Roman. / Random variate generation for discrete fuzzy numbers based on α-cuts. 2024 IEEE 7th International Conference on Big Data and Artificial Intelligence, BDAI 2024. Institute of Electrical and Electronics Engineers Inc., 2024. pp. 259-264 (2024 IEEE 7th International Conference on Big Data and Artificial Intelligence, BDAI 2024).

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title = "Random variate generation for discrete fuzzy numbers based on α-cuts",

abstract = "Probabilistic based random variate generation is the most popular method for representing randomness into simulation scenarios that could occur in real life. The main idea behind the use of random numbers to replicate the value of a uncertain variable can also be extended to fuzzy sets, including discrete fuzzy sets. This way, it is possible to use random numbers and the α -cut of a discrete fuzzy set to retrieve a random variate alongside its membership degree. To do so, a method for computing discrete fuzzy random variates based on α -cuts is proposed and applied to two examples: a comprehensive and a simulation example.",

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Figueroa-García, JC, Franco, C & Neruda, R 2024, Random variate generation for discrete fuzzy numbers based on α-cuts. in 2024 IEEE 7th International Conference on Big Data and Artificial Intelligence, BDAI 2024. 2024 IEEE 7th International Conference on Big Data and Artificial Intelligence, BDAI 2024, Institute of Electrical and Electronics Engineers Inc., pp. 259-264, 7th IEEE International Conference on Big Data and Artificial Intelligence, BDAI 2024, Beijing, China, 7/5/24. https://doi.org/10.1109/BDAI62182.2024.10692377

Random variate generation for discrete fuzzy numbers based on α-cuts. / Figueroa-García, Juan Carlos; Franco, Carlos; Neruda, Roman.
2024 IEEE 7th International Conference on Big Data and Artificial Intelligence, BDAI 2024. Institute of Electrical and Electronics Engineers Inc., 2024. p. 259-264 (2024 IEEE 7th International Conference on Big Data and Artificial Intelligence, BDAI 2024).

Research output: Chapter in Book/Inform › Conference contribution

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N2 - Probabilistic based random variate generation is the most popular method for representing randomness into simulation scenarios that could occur in real life. The main idea behind the use of random numbers to replicate the value of a uncertain variable can also be extended to fuzzy sets, including discrete fuzzy sets. This way, it is possible to use random numbers and the α -cut of a discrete fuzzy set to retrieve a random variate alongside its membership degree. To do so, a method for computing discrete fuzzy random variates based on α -cuts is proposed and applied to two examples: a comprehensive and a simulation example.

AB - Probabilistic based random variate generation is the most popular method for representing randomness into simulation scenarios that could occur in real life. The main idea behind the use of random numbers to replicate the value of a uncertain variable can also be extended to fuzzy sets, including discrete fuzzy sets. This way, it is possible to use random numbers and the α -cut of a discrete fuzzy set to retrieve a random variate alongside its membership degree. To do so, a method for computing discrete fuzzy random variates based on α -cuts is proposed and applied to two examples: a comprehensive and a simulation example.

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SP - 259

EP - 264

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Figueroa-García JC, Franco C, Neruda R. Random variate generation for discrete fuzzy numbers based on α-cuts. In 2024 IEEE 7th International Conference on Big Data and Artificial Intelligence, BDAI 2024. Institute of Electrical and Electronics Engineers Inc. 2024. p. 259-264. (2024 IEEE 7th International Conference on Big Data and Artificial Intelligence, BDAI 2024). doi: 10.1109/BDAI62182.2024.10692377

Random variate generation for discrete fuzzy numbers based on α-cuts

Abstract

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All Science Journal Classification (ASJC) codes

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