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• W2989182216 endingPage "106455" @default.
• W2989182216 startingPage "106455" @default.
• W2989182216 abstract "In this paper, a new method is proposed to deal with the interval model updating problem using universal grey mathematics and Gaussian process regression model (GPRM). The nonlinear relationship between the input and the output generally exists in the interval model updating problem, which has not been specially discussed in the current papers. In order to handle this issue better, the method concerned about the nonlinear monotonic relationship was proposed. It treats the interval model updating problem in a deterministic framework by universal grey mathematics. What’s more, GPRMs were used as the meta-model to improve computational efficiency. Two numerical examples and one experimental example were made in this paper: in the first numerical example, the method was validated using a three-degree-of-freedom spring-mass system; in the second numerical example, the ability of the method to deal with nonlinear problems was verified with a set of aluminum alloy plates; in the last experimental example, the experiment of a set of aluminum alloy plates was used to illustrate the method, where the thickness of the aluminum alloy plate was used as the updating parameter." @default.
• W2989182216 created "2019-11-22" @default.
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• W2989182216 date "2020-07-01" @default.
• W2989182216 modified "2023-10-12" @default.
• W2989182216 title "Interval model updating using universal grey mathematics and Gaussian process regression model" @default.
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• W2989182216 doi "https://doi.org/10.1016/j.ymssp.2019.106455" @default.
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