A Prediction Model of Gold Price Change Against US Dollar Based on BP Neural Network

Abstract

This project predicts the trend of gold price change against the US dollar and provides a more scientific and effective basis for investment decisions. The whole system is divided into two aspects: data visualization and BP neural network model application. For visualization and analysis, the powerful drawing function of Matlab was used for perspective drawing, and line graphs were created to show the degree of fit of the predicted values with the accurate values and the trend of change. For the BP neural network, the price prediction code based on the BP neural network was written using Matlab, and a prediction accuracy of 0.92230 was achieved by calculating the mean square error. The research results of this project provide a powerful price prediction tool based on neural network modeling, which will bring investors more accurate and objective information about price trends and provide more reliable and clearer prediction results to improve the success rate of investment.