IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/2780122.html
   My bibliography  Save this article

BP Neural Network Algorithm Based on Big Data for Monitoring and Early Warning of China’s Public Finance

Author

Listed:
  • Zongtao Zhao
  • Min Dong
  • Qian Bian
  • Wen-Tsao Pan

Abstract

Public finance plays an important role in the development and construction of the country. Public finance is derived from and used by the people. On the one hand, public finance mainly comes from national taxes and the income of some state-owned enterprises or state-owned assets. On the other hand, public finance is used for national infrastructure, military investment, scientific and technological research and development, national daily operation, and other expenses. Therefore, the state of public finance is closely related to people's lives, and it is also one of the basic symbols of a country's prosperity and strength. How to ensure that the country's public finance is in a good state, grasp the leverage balance of public finance revenue and expenditure, and avoid the situation of national “bankruptcy†is additional attention that the public finance department should pay in the process of operation. Therefore, we urgently need a set of public finance monitoring and early warning system that matches China's public finance operation mechanism and conforms to China's basic national conditions. At present, previous studies rely on the existing detailed data on public finance to measure the situation of China's public finance, but this method refers to fewer data and is not forward-looking enough. Therefore, this paper adopts a BP neural network algorithm to monitor and warn the situation of China's public finance based on computer big data.

Suggested Citation

  • Zongtao Zhao & Min Dong & Qian Bian & Wen-Tsao Pan, 2022. "BP Neural Network Algorithm Based on Big Data for Monitoring and Early Warning of China’s Public Finance," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-9, June.
  • Handle: RePEc:hin:jnlmpe:2780122
    DOI: 10.1155/2022/2780122
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/2780122.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/mpe/2022/2780122.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2022/2780122?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:2780122. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.