IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/4487654.html
   My bibliography  Save this article

Statistical Analysis of the Effect of Population Quality on Residents’ Income Distribution under the Data Fusion Algorithm

Author

Listed:
  • Lihua Wu
  • Xiaomei Guo
  • Xiao Zang
  • Xiantao Jiang

Abstract

After years of development, today’s society is a prosperous era of the knowledge economy. Different from the previous period of development by consuming natural resources, people have realized that talents with technology and knowledge have become an important factor in promoting the development of social production. That is to say, the improvement of population quality has not only an impact on its own development but also an important impact on the comprehensive strength and competitiveness of its location. Population quality is the stipulation of the population in terms of quality, also known as population quality. It includes ideological quality, cultural quality, physical quality, and so on. Data fusion is a technology for the comprehensive analysis and processing of information from multiple sources. Therefore, this paper comprehensively considers the influence of ideological and moral quality and population structure. Under the algorithm of fusion data, the impact of population quality on residents’ income is explored. This paper uses the analytic hierarchy process to weight each indicator and calculate the comprehensive score. This paper ranks the quality of population and economic development of each province, city, and autonomous region in China according to their high scores. The results of the experiments in this paper indicate a relevant analysis with the income distribution of the nation’s residents, and the correlation is −0.9493. There exists a negative relation between the overall quality of Chinese residents and the income gap.

Suggested Citation

  • Lihua Wu & Xiaomei Guo & Xiao Zang & Xiantao Jiang, 2022. "Statistical Analysis of the Effect of Population Quality on Residents’ Income Distribution under the Data Fusion Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-13, July.
  • Handle: RePEc:hin:jnlmpe:4487654
    DOI: 10.1155/2022/4487654
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/4487654.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/mpe/2022/4487654.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2022/4487654?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:4487654. 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.