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- W2893981465 abstract "For the characteristics of the fact that fault data samples of large phased array radar's T/R modules are not enough and the fluctuation of fault data is strong, grey neural network combination forecasting model is established to forecast the failure data. Firstly, in view of the issue that background value of traditional grey GM(l,l) model is solved by the average of the adj acent data, the area formed by exponential function and X-coordinate is used to solve the problem, then in view of the fact that data's weight of grey GM(l,l) model in different periods are the same, weight matrix is constructed to improve the accuracy of the model, then the improved grey GM(l,l) model and BP neural network model are combined in series and parallel, lastly, the availability is used to solve the weight of each forecasting model. The simulation results show that the model has high prediction accuracy and can provide theoretical basis for the maintenance and inventory strategy of T/R modules." @default.
- W2893981465 created "2018-10-05" @default.
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- W2893981465 date "2018-05-01" @default.
- W2893981465 modified "2023-09-23" @default.
- W2893981465 title "T/R Module's Failure Forecasting Model of Phased Array Radar Based on Grey Neural Network" @default.
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- W2893981465 doi "https://doi.org/10.1109/imcec.2018.8469458" @default.
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