Crude oil output forecasting based on PSO of unbiased gray Markov model

摘要

With the adjustment of China's energy strategy structure, the pace of oil exploration and development will be further accelerated, and how to accurately predict the trend of crude oil output is a problem worth studying [1]. In this paper, the traditional unbiased gray Markov model is used to fit the exponential sequence when there is a big deviation, and we proposed the particle swarm optimization algorithm to optimize this model. The optimal position of the particle is obtained by constantly updating the position of the particle. The optimal whitening coefficient is used to improve the prediction accuracy. We compare with the traditional forecasting model, the predicted results from unpredictable gray Markov chain with PSO has smaller relative error, and more accurate, which presents a new method for forecasting the output of crude oil.