The importance of crude oil in the world economy has made it imperative for efficient models to be designed for predicting future prices. This paper proposes an alternative approach based on a time series and biogeography-based optimization (BMMR–BBO) for the estimation of the West Texas Intermediate (WTI) crude oil price. To evaluate the forecasting ability of the presented model, we compared its performance with those of time series functions. The results of the experiment showed that BMMR-BBO performed better than the other methods and is a fairly good option for crude oil price prediction. The proposed model can be useful in the formulation of policies related to international crude oil price estimations, development plans, and industrial production.

原油在世界经济中的重要性使得必须设计有效的模型来预测未来价格。本文提出了一种基于时间序列和基于生物地理学的优化（BMMR-BBO）的替代方法，用于估算西德克萨斯中质原油（WTI）的原油价格。为了评估该模型的预测能力，我们将其性能与时间序列函数进行了比较。实验结果表明，BMMR-BBO比其他方法表现更好，是预测原油价格的不错选择。该模型可用于制定与国际原油价格估计，发展计划和工业生产有关的政策。