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Application of Bi-directional Elman Neural Networks in Satellite Battery Array Power’s Prediction(PDF)


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Application of Bi-directional Elman Neural Networks in Satellite Battery Array Power’s Prediction
GU Ji hai 1JIANG Xing wei 1WANG Xiao feng 2LONG Bing 1
1.School of Astronautics, Harbin Institute of Technology, Harbin 150001, China;2.School of Power Engineering,NUST,Nanjing 210094,China
Elman neural network bi-directional predict ion model satellite bat tery array pow er predict ion
In order to resolve the problem of determinat ion of the number of model order and predict ive accuracy being low in predict ing bat tery array power by ANN, the paper presents a bi-direct ional predict ive model based on improved Elman. Informat ion of future and past pre diction system is fused and memory of network for t ime-series feature’ s informat ion is strength ened by this model w hich depends on the feedback of connect ive lay er. T he method ef fect ively improves the predict ive accuracy. T he model presented by the paper needs not to determine the number of model order in predict ing bat tery array pow er. T he simulation results indicate that it s predict ive accuracy is greatly improved by comparison w ith unidirect ional model, and that the model has a bet ter generalization ability.


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Last Update: 2013-03-11