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Risk Assessment of Innovative Projects Based on Fuzzy Modeling

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Lecture Notes in Computational Intelligence and Decision Making (ISDMCI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1246))

Abstract

This article is devoted to the consideration of innovative risk assessment approach. The approach includes two stages. At the first stage, as a result of fuzzy network modeling, based on fuzzy linguistic assessments of duration and cost of the job, the size of initial investments and the projected duration of the initial period of the innovative process, using \(\beta \)-distribution, are determined. On the second, random scenarios are simulated and the possible risk is calculated. This procedure combines fuzzy estimates and the Monte Carlo simulation. Fuzzy estimates of the model parameters of possible results allow us to take into account the uncertainty of the initial information in the process of simulating random values. In this case, for modeling random variables, the Gauss membership function is used, which determines the distribution of expectations of input variables.

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Authors and Affiliations

  1. Taras Shevchenko National University of Kyiv, 64, Volodymyrska Street, Kyiv, 01033, Ukraine

    Yuri Samokhvalov

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  1. Yuri Samokhvalov
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Correspondence to Yuri Samokhvalov .

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Editors and Affiliations

  1. Department of Informatics, Jan Evangelista Purkyně University in Ústí nad Labem, Ústí nad Labem, Czech Republic

    Sergii Babichev

  2. Department of Informatics and Computer Science, Kherson National Technical University, Kherson, Ukraine

    Volodymyr Lytvynenko

  3. Institute of Electronics and Information, Lublin University of Technology, Lublin, Poland

    Waldemar Wójcik

  4. Department of Informatics and Computer Science, Kherson National Technical University, Kherson, Ukraine

    Svetlana Vyshemyrskaya

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Samokhvalov, Y. (2021). Risk Assessment of Innovative Projects Based on Fuzzy Modeling. In: Babichev, S., Lytvynenko, V., Wójcik, W., Vyshemyrskaya, S. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2020. Advances in Intelligent Systems and Computing, vol 1246. Springer, Cham. https://doi.org/10.1007/978-3-030-54215-3_17

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