摘要
为了准确预测企业财务长期变化趋势,文章提出一种基于ARIMA-LSTM的企业财务长期变化趋势预测算法。通过设计ARIMA算法模型,并结合LSTM模型架构,实现基于ARIMA-LSTM的企业财务长期变化趋势预测。实验发现文中所设计方法的预测准确性较高,拟合性能更优。
In order to accurately predict the long-term change trend of enterprise finance,a prediction algorithm for the long-term change trend of enterprise finance based on ARIMA-LSTM is proposed.By designing ARIMA algorithm model and combining with LSTM model architecture,the long-term change trend prediction of enterprise finance based on ARIMA-LSTM is realized.The experiment found that the designed method has high prediction accuracy and better fitting performance.
作者
杨静
刘炯
YANG Jing;LIU Jiong(School of Information and Finance,Xuancheng Vocational and Technical College,Xuancheng 242000,China)
出处
《湖北文理学院学报》
2024年第2期17-21,共5页
Journal of Hubei University of Arts and Science
关键词
自回归移动平均模型
长短期神经网络算法
企业财务
财务趋势
autoregressive mobile average model
long and short term neural network algorithm
enterprise finance
financial trend
