基于ARIMA-LSTM的企业财务长期变化趋势预测算法
A Prediction Algorithm for Long-term Change Trend of Enterprise Finance Based on ARIMA-LSTM
杨静 1刘炯1
作者信息
- 1. 宣城职业技术学院 信息与财经学院,安徽 宣城 242000
- 折叠
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.
Abstract
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.
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Key words
autoregressive mobile average model/long and short term neural network algorithm/enterprise finance/financial trend引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据