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- W2374443265 abstract "To reduce the power consumption of device,dynamic power management prediction strategies based on the structure of adaptive learning tree is researched.Through added idle-time length node in the structure model of Probability-based adaptive learning tree,an improved Prediction Strategies on the strength of Probability statistics weighted idle-time is proposed,the idle-time length is used as projections and based on the probability statistics of actual historical state,the idle-time predicted result is updated.Results of the simulation indicated the proposed method can effectively lower power consumption and improve the prediction accuracy." @default.
- W2374443265 created "2016-06-24" @default.
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- W2374443265 date "2013-01-01" @default.
- W2374443265 modified "2023-09-28" @default.
- W2374443265 title "Improved adaptive learning tree power management prediction strategies" @default.
- W2374443265 hasPublicationYear "2013" @default.
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