文章基本信息

标题：Design of Accounting Earnings Forecasting Model Based on Artificial Intelligence
本地全文：下载
作者：Jia Liu ; Shi Wu ; V. T. Pham 等
期刊名称：Scientific Programming
印刷版ISSN：1058-9244
出版年度：2022
卷号：2022
DOI：10.1155/2022/8793596
语种：English
出版社：Hindawi Publishing Corporation
摘要：The increasing complexity of the international situation intensifies the changes of the economic environment. People’s demand for information represented by accounting earnings, such as judging the profitability and risk coefficient of the company, is becoming more and more urgent. This study puts forward the theory of predicting accounting earnings through accounting earnings factors in a nonlinear way and designs an accounting earnings forecasting model based on artificial intelligence. Integrating LSTM, seq2seq, and reinforcement learning and combining with self-attention like mechanism, a complex multifactor time series forecasting model is established, and reinforcement learning is used to stabilize the model to prevent overfitting, which puts forward a new solution to the multifactor time series forecasting problem of complex relationship. The experimental results and comparative analysis show the effectiveness of the enhanced recurrent neural network accounting earnings prediction model designed in this study.