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TitleEvaluation model of enterprise operation based on BP neural network optimization algorithm
Creator
Date Issued2020-06-18
Source PublicationJournal of Physics: Conference Series
ISSN1742-6588
Volume1570
Issue1
AbstractThe parameter selection of the traditional BP neural network (BPNN) has randomness, which makes the network prone to local extreme values during the calculation process. In order to solve this problem, this paper introduces the bat algorithm(BA) to optimize the parameter selection process of the BPNN and apply the algorithm to evaluate the enterprises' operating condition, a corresponding evaluation model of the enterprises' operating condition is established, and the evaluation model is applied to the prediction of the enterprises' future operating condition and compared with the prediction effect of the traditional BPNN model. The prediction accuracy of the BPNN optimization algorithm is higher than the prediction accuracy of the traditional BPNN. The established enterprise operation evaluation model can effectively predict the future operation of the enterprise.
DOI10.1088/1742-6596/1570/1/012084
URLView source
Language英语English
Scopus ID2-s2.0-85088050824
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Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/6166
CollectionBeijing Normal-Hong Kong Baptist University
Corresponding AuthorZhang,Yan
Affiliation
1.Tongling University,Tongling, Anhui,244000,China
2.Beijing Normal University,Hong Kong Baptist University,United International College,Zhuhai, Guangdong,519000,China
3.University of Chinese Academy of Social Sciences,Beijing,102488,China
4.Chengdu University of Technology,ChengDu, Sichuan,610000,China
Recommended Citation
GB/T 7714
Zhang,Yan,Hu,Ziwei,Ji,Liet al. Evaluation model of enterprise operation based on BP neural network optimization algorithm[C], 2020.
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