Oil Price Forecasting Based on Particle Swarm Neural Network

Petroleum is one of the indispensable energy for development of world economy and politics. Oil price is affected by the situation of economy and diplomacy. The hybrid training algorithm is combined with the improved particle swarm optimization and BP algorithm, the improved PSO-BP ANN model is developed trained by the hybrid algorithm based on improved PSO and BP algorithm. According to problems of petroleum price prediction and the feasibility of petroleum price prediction model, the improved BP model for petroleum price prediction is proposed. It is shown that the proposed model is feasible and reliable to predict the petroleum price. Compared with conventional PSO-BP algorithm, the proposed algorithm has better accuracy and correlation.