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- W2951826005 abstract "Reliability-based design optimization under fuzzy and interval variables is important in engineering practice. The interval Monte Carlo simulation (IMCS), extremum method, and saddlepoint approximation (SPA) can be used for reliability optimization issues contain only interval variables. Thus, how to deal with the fuzzy variables is critical for system reliability analysis and optimization design. The α-level cut method can be applied to deal with fuzzy variables but it is complex and computationally expensive. Therefore, an equivalent conversion method based on entropy theory is proposed in this paper, which can convert the fuzzy variables to the normal random variables to avoid the complex integral process. According to the equivalent conversion method, the entropybased sequential optimization and reliability assessment (E-SORA) is developed in combination with the worst case analysis (WCA) for reliability-based design optimization under fuzzy and interval variables. A numerical example about the reliability design of the crank-link mechanism under fuzzy and interval variables is solved by the E-SORA, double-loops method, and α-level cut algorithm, respectively, is used to demonstrate the accuracy and efficiency, and the results show that the proposed method is feasible for reliability-based design optimization under fuzzy and interval variables" @default.
- W2951826005 created "2019-06-27" @default.
- W2951826005 creator A5037335978 @default.
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- W2951826005 date "2019-09-30" @default.
- W2951826005 modified "2023-10-16" @default.
- W2951826005 title "Reliability-based design optimization under fuzzy and interval variables based on entropy theory" @default.
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- W2951826005 doi "https://doi.org/10.17531/ein.2019.3.9" @default.
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