基于神经网络的石油价格预测  

Oil Price Forecasting Using Neural Networks Method

作　　者：孙大利[1] 来君[1] 

机构地区：[1]浙江大学,浙江杭州310027

出　　处：《石油化工高等学校学报》2006年第2期89-92,共4页Journal of Petrochemical Universities

摘　　要：当前石油价格研究在石油价格数据选择、数据预处理和预测方法选择上存在数据时段选择不当、直接套用原始数据代入模型以及价格预测模型和训练数据类型不相匹配等问题,需要予以解决。在采用同期通货膨胀率指数调整、滑动平均周期项以及随机项滤波等方法对石油价格时间序列数据进行预处理的基础上,利用神经网络方法,以纽约商品交易所(NYMEX)为例对轻质原油期货即期价格时间序列数据建立预测模型。最后用油价波动趋势进行拟合分析,将预处理后的石油价格时间序列数据输入到神经网络预测模型,模型的预测结果和直接套用原始数据得到的预测结果相比较,其平均偏差率显著降低。At present, there are some mistakes in choice, pretreatment and forecasting of time series data of oil price in some researches, such as improper data set, using raw data indiscriminately and improper model corresponding to data set, which need to be improved. Using inflation rate adjustment, moving- average method and stochastic filter, oil future front price data series was pretreated. Based on this a forecast model of time series oil price about NYMEX was presented with BP neural networks. In the end, the oil price fluctuation trend was analyzed. The processed oil price time series datas were inputed into neural networks forcasting model. The forecasting results between raw data and proce.ssed data using neural networks was compared and the latter effect is better, and the average deviation rate remarkably reduced

关 键 词：石油价格 时间序列 神经网络 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] F062.1[自动化与计算机技术—控制科学与工程]