Research on Gold Demand Prediciton Based on GM-GPR Model

The prediction system of gold demands in China is faced with issues such as uncertain factors, limited historical data, and nonlinearity. In order to have a more accurate demands, method based on the integration grey Gaussian process regression proposed. Specifically, equal weights are assigned each model adopted reflect changing relationship indicating nonlinear impacts factors demands. Moreover, modified particle swarm optimization plays role optimizing hyper-parameters regression, which solves issue that conjugate gradient algorithms depend initial value setting susceptible be confined by locally optimal solutions. According study, proposal paper superior separate or terms better predicting