Crude oil being a significant source of energy, change of crude oil price can affect the global economy. In this paper, a new approach based on the intuitionistic fuzzy set theory has been implemented to predict the crude oil price. This paper presents the intuitionistic fuzzy time series forecasting algorithm to enhance the efficacy of time series forecasting which includes fuzzy c-means clustering to obtain the optimal cluster centers. Further, a computational technique is proposed for the construction of triangular fuzzy sets and these fuzzy sets are converted to intuitionistic fuzzy sets with the help of Sugeno type intuitionistic fuzzy generator. The popular benchmark dataset of West Texas Intermediate crude oil spot price is used for the validation process. The numerical results when compared with existing methods notify that the proposed method enhances the accuracy of the crude oil price forecasts. KeywordsIntuitionistic fuzzy set, Sugeno type complement function, Fuzzy c-means clustering, Crude oil price forecasting, Fuzzy time series.

中文翻译：

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基于Sugeno直觉模糊发生器的原油价格预测计算技术。

原油是重要的能源，原油价格的变化会影响全球经济。本文采用了一种基于直觉模糊集理论的新方法来预测原油价格。本文提出了一种直观的模糊时间序列预测算法，以提高时间序列预测的有效性，该算法包括模糊c均值聚类以获得最优聚类中心。此外，提出了一种用于构建三角模糊集的计算技术，并借助Sugeno型直觉模糊生成器将这些模糊集转换为直觉模糊集。验证过程使用了西德克萨斯中质原油现货价格的受欢迎基准数据集。与现有方法比较的数值结果表明，该方法提高了原油价格预测的准确性。直觉模糊集Sugeno型补函数模糊c均值聚类原油价格预测模糊时间序列