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- W2350156847 abstract "According to the nonlinear and non-stationary characteristics of hydroelectric sets vibration,this paper proposes a general regression network(GRNN) model based on fruit fly optimization algorithm(FOA) and achieves the optimal choice of GRNN distribution parameters.The model is applied to vibration peak-peak value trend prediction in 5 different parts of 3 hydroelectric sets in Sichuan Xinzhenghangdian Hydropower Station.Comparison of mean squared error between BP and GRNN,the results show that GRNN can improve prediction precision." @default.
- W2350156847 created "2016-06-24" @default.
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- W2350156847 date "2012-01-01" @default.
- W2350156847 modified "2023-09-23" @default.
- W2350156847 title "Condition Trend Prediction of Hydroelectric Sets Based on Fruit Fly Optimization Algorithm Optimized GRNN" @default.
- W2350156847 hasPublicationYear "2012" @default.
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