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- W4382936259 abstract "This paper is concerned with the problem of machine failure rate identification of a 3-state reparable system and its implementation via deep learning. The mathematical model is governed by a distributed parameter system involving coupled partial and integro-differential equations. The objective of this work is to identify the failure rates using the sampled system output measurements. Deep learning based failure rate identification methods are proposed. Numerical examples are provided to illustrate the designs and results." @default.
- W4382936259 created "2023-07-04" @default.
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- W4382936259 date "2023-05-31" @default.
- W4382936259 modified "2023-09-26" @default.
- W4382936259 title "Failure Rate Identification of a Reparable System Governed by Coupled ODE-PDEs and Deep Learning based Implementation" @default.
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- W4382936259 doi "https://doi.org/10.23919/acc55779.2023.10156339" @default.
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