Introduction - If you have any usage issues, please Google them yourself
The structure of three-layer BP neural network is adopted. The number of neurons in the input layer is 5, the number of neurons in the hidden layer is 3, and the number of neurons in the output layer is 1.
The data are divided into training sample set and testing sample set according to 14:1. After testing and analysis, the prediction error is 0.1700 and the error is small.
After network training, input six sets of data from the previous day, namely, the highest price, the lowest price, the opening price, the closing price and the volume, and then automatically predict the closing price of the next day.