基于LSTM神经网络的饲料企业财务风险预警模型构建  

Construction of feed enterprise financial risk early warning model based on LSTM neural network

作　　者：杨旭[1] 黄雪梅[1] YANG Xu;HUANG Xuemei(Chongqing College of Finance and Economics,Chongqing City 402160,China)

机构地区：[1]重庆财经职业学院,重庆市402160

出　　处：《中国饲料》2022年第14期135-138,共4页China Feed

基　　金：2021年重庆市教育科学规划项目(2021-GX-421)。

摘　　要：随着饲料行业多元化加速发展,受市场、外界竞争环境等客观因素的影响,饲料企业的风险也在逐步增加。为保障饲料企业的稳步发展,借助LSTM神经网络相关算法积极构建饲料企业财务风险预警模型具有重要意义。本文立足饲料企业当前发展的实际情况,选取饲料企业财务风险预警的因素指标,通过LSTM神经网络算法输出基于LSTM的饲料企业财务风险预警模型的风险预警值,为饲料企业财务风险预警提供参考。验证发现,相对于其他通用的预警模式来讲,基于LSTM神经网络的饲料企业财务风险预警模型更具准确性。With the rapid development of feed industry diversification,the risks of feed enterprises are gradually increasing due to the impact of objective factors such as the market and the external competitive environment.In order to ensure the steady and sustainable development of feed enterprises,it is of great significance to actively build a feed enterprise financial risk early warning model with the help of relevant algorithms of LSTM neural network.Based on the actual development of feed enterprises,this paper selects the factor indicators of feed enterprise financial risk early warning,and outputs the risk early warning value of feed enterprise financial risk early warning model based on LSTM neural network algorithm,so as to provide reference for feed enterprise financial risk early warning.It is found that compared with other common early warning models,the feed enterprise financial risk early warning model based on LSTM neural network is more accurate.

关 键 词：LSTM神经网络 饲料企业 财务风险预警 模型构建 

分 类 号：F3[经济管理—产业经济]