Abstract
This article presents the mechanisms for processing fuzzy expert estimates in network models for project management. The distribution of the probability function of the execution time is proposed. This function allows us to build a \( \beta \)-distribution of a random variable over the entire domain of its definition for a combination of approximate points and interval expert estimates. This article describes also the approximation of linguistic estimates by using fuzzy triangular and trapezoidal numbers. It is based on the construction of the membership function of a fuzzy triangular number, accounting for its scale. The proposed approach makes it possible to obtain more accurate prediction estimates for making informed decisions during informational uncertainty.
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Samokhvalov, Y. (2020). Construction of the Job Duration Distribution in Network Models for a Set of Fuzzy Expert Estimates. In: Lytvynenko, V., Babichev, S., Wójcik, W., Vynokurova, O., Vyshemyrskaya, S., Radetskaya, S. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2019. Advances in Intelligent Systems and Computing, vol 1020. Springer, Cham. https://doi.org/10.1007/978-3-030-26474-1_8
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DOI: https://doi.org/10.1007/978-3-030-26474-1_8
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