基于神经网络算法的上市企业经济效益评估方法研究  

Research on Economic Benefit Evaluation Method of Listed Enterprises Based on Neural Network Algorithm

作　　者：李男男[1] LI Nannan(Department of Plan and Finance,Shantou Polytechnic,Shantou 515078,China)

机构地区：[1]汕头职业技术学院计划财务处,广东汕头515078

出　　处：《河南财政金融学院学报(自然科学版)》2024年第4期29-34,共6页Journal of Henan Finance University(Natural Science Edition)

基　　金：广东省哲学社会科学规划项目(GD23YDXZYJ05)。

摘　　要：为有效解决传统经济效益评估方法存在评估结果不准确以及评估效率较低等问题,提出一种基于神经网络算法的上市企业经济效益评估方法。分析上市企业的经济发展情况,获取经济指标。将上市企业经济指标作为神经网络的输入数据,采用优化后的神经网络对上市企业经济效益进行评估和分析。实验结果表明,该方法能够有效降低经济效益评估时间和评估费用,提升评估结果的准确性。In order to effectively solve the problems of inaccurate evaluation results and low evaluation efficiency in traditional economic benefit evaluation methods,a method of economic benefit evaluation for listed enterprises based on neural network algorithm is proposed.Analyzed the economic development of listed enterprises and obtained economic indicators.Taking the economic indicators of listed enterprises as input of neural network,the optimized neural network is used to evaluate and analyze economic benefits of listed enterprises.The experiment results show that the proposed method can effectively reduce the time and cost of economic benefit evaluation and improve the accuracy of evaluation results.

关 键 词：神经网络算法 上市企业 经济效益 评估方法 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]