Affiliation:
1. Business School, Fuzhou Institute of Technology, Fuzhou 350506, China
2. Saigon University, Ho Chi Minh, Vietnam
Abstract
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.
Funder
2019 Fujian Young and Middle-Aged Teacher Education Research Project
Subject
Computer Science Applications,Software
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