Accounting Data Quality Evaluation Method Based on Improved Particle Swarm Algorithm. (20th January 2022)

• Record Type: Journal Article
• Authors: Sun, Mengying
• Other Names: Li Qiangyi Academic Editor.
• Is Part Of: Advances in multimedia. Volume 2022(2022)
• Publication Date: 2022-01-20
• Subjects: Multimedia systems -- Periodicals; Computer networks -- Periodicals; Multimédia; Réseaux d'ordinateurs; Computer networks; Multimedia systems; Periodicals; 006.7
• DOI: 10.1155/2022/3859994
• Languages: English
• ISSNs: 1687-5680

Abstract

Abstract : With the continuous improvement of the capital market and related laws and regulations, accounting as a reflection of the corporate capital movement will have a significant impact on the quality of the entire accounting information. Moreover, for investors, whether accounting information can meet their needs is an important basis for assessing the feasibility of investment projects. Therefore, the importance of accounting information is becoming more and more important, and it has gradually become the focus of attention of all parties. In order to improve the effect of accounting quantity and quality evaluation, this article improves the particle swarm optimization algorithm. It improves the particle swarm optimization algorithm from the three aspects—extreme value selection, particle diversity, and inertia weight, and establishes an optimization algorithm suitable for solving the accounting data audit optimization problem. The experimental research results show that the accounting data quality evaluation system based on the improved particle swarm algorithm proposed in this article has a good accounting data quality evaluation effect and meets the basic requirements of this article to build the system.