Correlation analysis of financial indicators and stock price fluctuations based on artificial intelligence system

Correlation analysis of the financial indicators and stock price fluctuations based on artificial intelligence system. In GANs artificial neural network, the number of GANs artificial neurons in the middle layer is required to be the same as the number of training samples, and each GANs artificial neuron stores one training sample, which is called direct memory artificial neuron. The adjustment of connection weights more accurately approximates the nonlinear mapping relationship reflected in the stock market price fluctuations, so as to realize the short-term accurate prediction of the stock market price. This research work has designed the novel neural network model to construct the ideas of the prediction model. Compared with the state-of-the-art ways, the performance is satisfactory.