Research on the Financial Support Performance Evaluation of Big Data Industry Development
Wenyu Fu,
Jingfeng Zhao,
Changming Wang,
Xiaobin Zhou and
Hengchang Jing
Mathematical Problems in Engineering, 2022, vol. 2022, 1-9
Abstract:
In order to solve the problem that the traditional information systems have such as slow running responses and cannot meet the expected requirements of users, a performance evaluation method of financial support for the development of the big data industry is proposed. According to the characteristics of financial support, this paper uses the analytic hierarchy process (AHP) and the fuzzy comprehensive evaluation principle to establish a specific evaluation index system for the performance evaluation of financial support in the big data industry and select a suitable index group. In order to reflect the financial support performance, the analytic hierarchy process (AHP) is used to calculate the weight of various performance evaluation indicators, and the fuzzy comprehensive evaluation is used to combine qualitative analysis and quantitative analysis to evaluate and calculate the big data industry scientifically, objectively, fairly, and accurately. In financial support performance, experiments show that the proposed method not only has a fast response time but also can ensure that the actual results after the system runs are in line with the expectations of the system users.
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/mpe/2022/1972726.pdf (application/pdf)
http://downloads.hindawi.com/journals/mpe/2022/1972726.xml (application/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1972726
DOI: 10.1155/2022/1972726
Access Statistics for this article
More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().