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A Deep Convolutional Neural Network Based Risk Identification Method for E-Commerce Supply Chain Finance
Tang, Qian1,2; Lu, Yan2; Wang, Bin1; Li, Zhen3,4
2022-04-14
Source PublicationSCIENTIFIC PROGRAMMING
ISSN1058-9244
Volume2022Pages:6298248
Abstract

With the popularity of the Internet, the rise of e-commerce platforms has led to the rapid development of supply chain (SC) financial services in China, and the competitiveness of commercial banks and core enterprises in the supply chain is now gradually increasing, rapidly expanding into an important area of competition between the two. As an emerging force rebounding from the economic downturn, e-commerce platform transactions, with their unique characteristics of informatization, diversification, and convenience, have provided a broad space for Internet SC finance. The article mainly analyzes the risk identification method of e-commerce SC finance, analyzes its risk from the financing process, gives corresponding data support for the matters or processes that may cause financing risk based on DCNN model, and takes Jingdong SC finance as an example and analyzes its main financing methods and risk identification process; based on different experimental comparisons, a multigroup experimental study shows that the accuracy of supply chain finance risk identification using deep convolutional neural network models can reach 95.36%, which demonstrates the effectiveness of the proposed method by providing better performance compared to traditional BP and SVM networks.

DOI10.1155/2022/6298248
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Software Engineering
WOS IDWOS:000806209500004
PublisherHINDAWI LTD
Scopus ID2-s2.0-85129078814
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionFaculty of Social Sciences
Corresponding AuthorLi, Zhen
Affiliation1.Faculty of Science and Technology, University of Macau, Taipa, 999078, Macao
2.College of Business, Beijing Institute of Technology, Zhuhai, Guangdong, 519088, China
3.Centre for Efficiency and Performance Engineering, University of Huddersfield, Huddersfield, HD1, United Kingdom
4.College of Industrial Automation, Beijing Institute of Technology, Zhuhai, Guangdong, 519088, China
First Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Tang, Qian,Lu, Yan,Wang, Bin,et al. A Deep Convolutional Neural Network Based Risk Identification Method for E-Commerce Supply Chain Finance[J]. SCIENTIFIC PROGRAMMING, 2022, 2022, 6298248.
APA Tang, Qian., Lu, Yan., Wang, Bin., & Li, Zhen (2022). A Deep Convolutional Neural Network Based Risk Identification Method for E-Commerce Supply Chain Finance. SCIENTIFIC PROGRAMMING, 2022, 6298248.
MLA Tang, Qian,et al."A Deep Convolutional Neural Network Based Risk Identification Method for E-Commerce Supply Chain Finance".SCIENTIFIC PROGRAMMING 2022(2022):6298248.
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