A Stock Forecasting Method Based on Attention Mechanism and Feature Fusion
A new stock prediction method called AFG is proposed based on the application of artificial intelligence in financial data.AFG uses position encoding and time encoding to obtain the position and time information of stock data,and then extracts features from the stock data separately through gated loop units and multi head self attention mechanisms.After fusing the features of the two types of stocks,the final stock prediction curve is derived from the fully connected layer.
stock predictiongate control loop unitattention mechanismlocation codingtime coding
万方数据
维普
