Acta Metrologica Sinica  2012, Vol. 33 Issue (6): 546-549    DOI: 10.3969/j.issn.1000-1158.2012.06.15
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BP Neural Networks Based on Adaptive Genetic Algorithms and Its Application to Prediction of Battery Capacity
FENG Nan,WANG Zhen-chen,PANG Ying
Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004, China
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Abstract  A model is created by adopting BP neural network to predict the state of charge of battery, and adaptive genetic algorithm(AGA) is utilized to optimize its weights and bias, to analyze many factors that affecting the battery residual capacity.Finally, with the emulation program written by MATLAB, multiple sets of data are tested and compared with pure BP network and GA-BP network.The results show that the AGA-BP network has a short training time and high accuracy. It is effective for prediction of the any state battery capacity.
Key wordsMetrology      Battery capacity      BP neural network      Adaptive genetic algorithm     
PACS:  TB971  
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FENG Nan
WANG Zhen-chen
PANG Ying
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FENG Nan,WANG Zhen-chen,PANG Ying. BP Neural Networks Based on Adaptive Genetic Algorithms and Its Application to Prediction of Battery Capacity[J]. Acta Metrologica Sinica, 2012, 33(6): 546-549.
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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2012.06.15     OR     http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2012/V33/I6/546
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