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本科毕业论文(设计)
论文题目:人工神经网络在时间序列预测中的应用研究

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人工神经网络在时间序列预测中的应用研究
内容摘要
时间序列是将某种统计指标的数值,按时间先后顺序排列所形成的数列。时间序列预测的内容包括:收集与整理某种社会现象的历史资料;对这些资料进行检查鉴别,排成数列;分析时间数列,从中寻找该社会现象随时间变化而变化的规律,得出一定的模式;以此模式去预测该社会现象将来的情况。
时间序列预测有很多方法,人工神经网络作为一种新的时间序列预测方法,以其良好的非线性性质、并行分布式的存储结构和高容错性等特点在很多实际应用领域中都取得了成功。
本文通过对人工神经网络以及时间序列预测的学习,建立 BP神经网络模型对石油期货价格进行预测,实验证明用人工神经网络进行时间序列预测数据拟合度高,预测效果较好。
关键词:人工神经网络时间序列预测 BP网络
Artificial works in Time Series Prediction
Abstract
Time series is a statistical indicator of value, by the time the order in which they formed with the series. The course content includes: collecting and collating the history of a social phenomenon of information; of these data to check identification, line series; analysis of time series, from the social phenomenon of looking for changes over time the e to a certain degree of model; to this model to predict the social phenomenon of the future.
There are many time series forecasting methods, artificial work as a new time-series forecasting methods, its non-linear nature of good, parallel distributed memory structure and fault tolerance features such as high in many areas of practical applications have been made ess.
This article on artificial works and time series prediction of the study, the establishment of BP work model to predict the price of oil futures, experimental proof of artificial works with time-series forecast error less effective.
Key words:Artificial work Time Series Prediction work

目录
序言 5
一、研究背景和意义 6
(一)时间序列预测 6
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(二)石油期货 7
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二、时间序列预测的理论和方法 9
(一)时间序列预测的步骤 9
(二)时间序列预测方法 9
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(三)人工神经网络 10
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三、BP网络 17
(一)BP网络 17
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(二)BP网络的学习算法 18
(三)BP网络设计 19
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