关键词: 价格预测, 量子粒子群算法, 量子粒子群算法（QPSO）-反向传播（BP）模型, 铀价

Abstract: Changes in the price of uranium products directly determine the value of the uranium project. The uranium price forecasting can improve business decision-making ability and the ability to resist risks. In order to improve the generalization ability of BP network to predict the price of U3O8, a QPSO-BP model is proposed. This model uses the QPSO to optimize the initial value of weights and thresholds of BP network. The position vector of the individual particle searched in global space is encoded as the best optimized value of weights and thresholds used in the 5-11-1 streamlined structure to predict the price of U3O8. The experiments show that the BP network optimized by QPSO can produce a stable prediction result, and its ARV is 0.0025. QPSO-BP model is more stable with its relative error mainly below 1%. Compared with the PSO-BP and BP prediction models, the generalization ability is better than the first two models, and the prediction accuracy with a least value（0.151%）. The  result indicates that the QPSO-BP model is effective and can be applied in uranium price forecasting, and also provides some reference value for the policy decision for mining project investment.

Key words: price forecast, Quantum Particle Swarm Optimization（QPSO）algorithm, Quantum Particle Swarm Optimization(QPSO)-Back Propagation（BP） model, uranium price