摘要
石油价格的走势一直是世界各国所研究和关注的焦点,石油期货是世界石油交易的一种重要方式,准确预测石油期货价格的走势,对于政府宏观政策取向和相关企业经营决策具有重要意义。本文利用BP神经网络的自适应学习能力,建立基于LM算法的石油期货价格预测模型,并使用MATLAB7.0编程实现,针对纽约商业交易所的石油期货价格数据进行了训练和测试。研究结果表明,将基于LM算法的BP神经网络模型应用于石油期货价格预测中,运算速度快,预测精度高,具有推广应用的价值。
The trend of petroleum prices has been the focus of study around the world, petroleum futures is an important way of the world＇s petroleum transactions. For the government＇s macroeconomic policy and related businesses decision-making, accurately prediction of the petroleum futures price＇s trend is important. Using BP neural network＇s adaptive learning capability and MATLAB 7.0 programming, build neural network prediction model based on LM algorithm for training and testing New York Mercantile Exchange＇s petroleum futures price. The results indicate that BP neural network model based on the LM algorithm applied into the petroleum futures price forecasting have many advantages such as fast computing speed, good forecasting precision and the value of promotion and application.
出处
《技术经济与管理研究》
北大核心
2009年第5期19-21,共3页
Journal of Technical Economics & Management
基金
陕西省自然科学基金(编号:2007F25)
西安财经学院重点项目基金(编号:08xcj005)
关键词
LM算法
神经网络
石油期货价格
预测
LM algorithm
neural network
petroleum futures price
prediction
