|Table of Contents|

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

《南京理工大学学报》（自然科学版）[ISSN:1005-9830/CN:32-1397/N]

Issue:
2004年04期
Page:
404-408
Research Field:
Publishing date:

Info

Title:
Application of Bi-directional Elman Neural Networks in Satellite Battery Array Power’s Prediction
Author(s):
GU Ji hai 1; JIANG Xing wei 1; WANG Xiao feng 2; LONG Bing 1
1.School of Astronautics, Harbin Institute of Technology, Harbin 150001, China;2.School of Power Engineering,NUST,Nanjing 210094,China
Keywords:
Elman neural network;  bi-directional predict ion model;  satellite bat tery array pow er;  predict ion
PACS:
V44
DOI:
-
Abstract:
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.

References:

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Last Update: 2013-03-11