期刊名称：International Journal of Computer Information Systems and Industrial Management Applications
印刷版ISSN：2150-7988
电子版ISSN：2150-7988
出版年度：2015
卷号：7
页码：053-065
出版社：Machine Intelligence Research Labs (MIR Labs)
摘要：Crude oil price prediction is a challenging task due to its complex nonlinear and chaotic behavior. There is a great need for oil price volatility measuring and modeling of oil price chaotic behavior. During the last couple of decades, both academicians and practitioners have devoted proactive knowledge to address this issue. Combined predictors are one of the most promising forms in Machine learning (ML). It can be found in different styles in the literature such as Meta learning, Ensemble based prediction, Hybrid methods and more. The aim of this paper to conduct comprehensive comparisons among the combined prediction model in order to improve the performance
关键词：Crude oil prediction; Meta prediction models; Hybrid ; models; Ensemble prediction model; ANFIS; P SO
