Storage Life Forecasting for Missiles Based on Improved Gray Model and RBF Optimization Model

doi:10.3969/j.issn.1006-2475.2015.08.008

Abstract

Abstract: The combined forcasting model based on the gray model and RBF neural network optimization model was proposed, for solving the problem of little failure data in storage period and difficult to forecast, and the combined model was established to forecast the storage life of missiles. The result shows that the combined model is better than the single forecasting model, and is regarded of high practice value.
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Key words: life evaluation, gray theory, neural network, combined method, missiles

CLC Number:

TP181

]XU Ting-xue 1, ZHU Hui-chuan2, DONG Qi2. Storage Life Forecasting for Missiles Based on Improved Gray Model and RBF Optimization Model[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2015.08.008.

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