文章基本信息

标题：Machine Learning Approach for Predicting Crude Oil Price Using Fuzzy Rule Based Time Series Method and Sentimental Analysis
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作者：Dona Sara Jacob ; Sam G Benjamin ; Radhakrishnan B 等
期刊名称：International Journal of Computer Science and Network
印刷版ISSN：2277-5420
出版年度：2019
卷号：8
期号：3
页码：262-265
出版社：IJCSN publisher
摘要：The movements in oil prices are very complex and, therefore, seem to be unpredictable. The continuous usage of statistical and econometric techniques for crude oil price prediction might demonstrate demotions to the prediction performance. Crude oil price prediction depends on heavily on uncertainty in the crude oil price fluctuation. The proposed approach uses a fuzzy rule based system embedded in fuzzy time series application to accurately extract a feature weight that can predict crude oil price prediction accurately. Another major parameter used for crude oil price prediction is news feeds. Our proposed approach extracts features weights from news feeds using a sentimental analysis based on latent dirichlet allocation topic model that can distinguish various online news topics. Both these feature weights along with the quantitative key factors are feed in to recurrent neural network.
关键词：Crude oil price prediction; fuzzy rule based system; sentimental Analysis; Latent Dirichlet Allocation topic Model