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首页> 外文会议>International Symposium on Knowledge and Systems Sciences(KSS2004); 20041110-12; Ishikawa(JP) >Crude Oil Price Forecasting with TEI@I Methodology
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Crude Oil Price Forecasting with TEI@I Methodology

机译：用TEI @ I方法进行原油价格预测

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摘要

The difficulty in crude oil price forecasting, due to inherent complexity, has attracted much attention of academic researchers and business practitioners. Various methods have been tried to solve the problem of forecasting crude oil prices. However, all of the existing models of prediction can not meet practical needs. In this study, a new methodology for handling complex systems - TEI@I methodology is proposed by means of a systematic integration of text mining, econometrics and intelligent techniques. Within the framework of TEI@I methodology, econometrical models are used to model the linear components of crude oil price time series (i.e., main trends) while nonlinear components of crude oil price time series (i.e., error terms) are modeled by using artificial neural network (ANN) models. In addition, the impact of irregular and infrequent future events on crude oil price is explored using web-based text mining (WTM) and rule-based expert systems (RES) techniques. Thus, a fully novel nonlinear integrated forecasting approach with error correction and judgmental adjustment is formulated to improve prediction performance within the framework of the TEI@I methodology. The proposed methodology and the novel forecasting approach are illustrated via an example.
机译：由于固有的复杂性，原油价格预测中的困难引起了学术研究人员和商业从业人员的极大关注。已经尝试了各种方法来解决预测原油价格的问题。但是，所有现有的预测模型都无法满足实际需求。在这项研究中，通过对文本挖掘，计量经济学和智能技术的系统集成，提出了一种处理复杂系统的新方法-TEI @ I方法。在TEI @ I方法论的框架内，使用计量经济学模型对原油价格时间序列的线性成分（即主要趋势）进行建模，而对原油价格时间序列的非线性成分（即误差项）进行人工建模。神经网络（ANN）模型。此外，使用基于Web的文本挖掘（WTM）和基于规则的专家系统（RES）技术，探索了不定期和不经常发生的未来事件对原油价格的影响。因此，在TEI @ I方法论的框架内，提出了一种具有误差校正和判断调整的完全新颖的非线性综合预测方法，以提高预测性能。通过示例说明了所提出的方法和新颖的预测方法。

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