Disclosure Model of Capital Accounting Information Based on Immune Particle Swarm Optimization Algorithm

4区 医学
Yu-Ting Ni
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Abstract

The effectiveness of capital market and the allocation of social resources depend on the disclosure of capital accounting information. In order to analyze the tendency of capital accounting information disclosure, this paper proposes a disclosure model of capital accounting information based on immune particle swarm algorithm. There are many factors that affect the tendency of capital accounting information disclosure. We should give priority to corporate governance level and financial status level to construct the impact index system of capital accounting information disclosure. The capital accounting information disclosure model was constructed to establish the functional relationship between each factor variable and disclosure tendency. Particle concentration was maintained through immune memory and self-regulation mechanism to ensure the diversity of the population, which avoids the traditional shortcomings of particle swarm optimization algorithm. Finally, the parameter estimation of capital accounting information disclosure model were completed. The results show that there are four factors affecting the disclosure tendency of capital accounting information, including ownership structure, leverage, growth and audit opinion. The accuracy of the model used in this paper is up to 75%.
基于免疫粒子群优化算法的资本会计信息披露模型
资本会计信息的披露关系到资本市场的有效性和社会资源的配置。为了分析资本会计信息披露的趋势,提出了一种基于免疫粒子群算法的资本会计信息披露模型。影响资本会计信息披露倾向的因素有很多。构建资本会计信息披露影响指标体系应从公司治理层面和财务状况层面入手。构建资本会计信息披露模型,建立各因素变量与披露倾向之间的函数关系。通过免疫记忆和自我调节机制维持粒子浓度,保证种群的多样性,避免了传统粒子群优化算法的不足。最后,完成了资本会计信息披露模型的参数估计。结果表明,影响资本会计信息披露倾向的因素有股权结构、杠杆率、成长性和审计意见四个方面。本文所采用的模型精度可达75%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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