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基于ARIMA-LSTM的企业财务长期变化趋势预测算法

杨静 刘炯

湖北文理学院学报2024,Vol.45Issue(2):17-21,5.
湖北文理学院学报2024,Vol.45Issue(2):17-21,5.

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

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

分类

信息技术与安全科学

引用本文复制引用

杨静,刘炯..基于ARIMA-LSTM的企业财务长期变化趋势预测算法[J].湖北文理学院学报,2024,45(2):17-21,5.

湖北文理学院学报

OACHSSCD

2095-4476

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