人工神经网络在时间序列预测中的应用研究论文(5[1].22)

2019-03-28 11:05

本科毕业论文(设计)模板 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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完成日期: 年 月 日

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

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Artificial Neural Networks 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 rules come 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 neural network 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 success.

This article on artificial neural networks and time series prediction of the study, the establishment of BP neural network model to predict the price of oil futures, experimental proof of artificial neural networks with time-series forecast error less effective.

Key words:Artificial Neural Network Time Series Prediction BP network

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目录

序言 ................................................................................................... 5 一、研究背景和意义 ..................................................................... 6

(一)时间序列预测....................................................................................... 6

1.时间序列.................................................................................................... 6 2.时间序列预测............................................................................................ 6

(二)石油期货 ................................................................................................ 7

1.石油期货的市场运作条件........................................................................ 7 2.石油期货价格波动的多种因素................................................................ 7 3.中国石油期货现况.................................................................................... 8 4.石油期货预测的意义................................................................................ 8

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

1.支持向量机方法........................................................................................ 9

2.小波分析法.............................................................................................. 10 3.回归分析法.............................................................................................. 10 4.灰色系统.................................................................................................. 10 5.人工神经网络法...................................................................................... 10

(三)人工神经网络..................................................................................... 10

1.人工神经网络的特点和优越性...............................................................11 2.人工神经网络的学习方式...................................................................... 12 3.人工神经网络的分类.............................................................................. 12 4.人工神经网络在时间序列预测中的优势.............................................. 16

三、BP网络 .................................................................................. 17

(一)BP网络 ................................................................................................ 17

1.BP网络模型............................................................................................ 17 2.BP网络的应用........................................................................................ 17

(二)BP网络的学习算法 ......................................................................... 18 (三)BP网络设计 ....................................................................................... 19

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1.网络层数.................................................................................................. 19 2.输入层的节点数...................................................................................... 19 3.输出层的节点数...................................................................................... 20 4.隐层的节点数.......................................................................................... 20 5.传输函数.................................................................................................. 20

四、时间序列预测实验 ............................................................... 21

(一)MATLAB ............................................................................................. 21

1.MATLAB简介 ........................................................................................ 21 2.MATLAB的特点 .................................................................................... 21 3.MATLAB的应用 .................................................................................... 21 4.MATLAB的优势 .................................................................................... 21

(二)BP神经网络的MATLAB实现.................................................... 22

1.生成一个BP网络................................................................................... 22 2.BP网络的训练........................................................................................ 23 3.BP神经网络的仿真................................................................................ 23 4.BP网络的预处理和后处理函数............................................................ 23

(三)预测实验 .............................................................................................. 24

1.移动窗口原理.......................................................................................... 24 2.建立实验模型.......................................................................................... 25 3.选取实验数据.......................................................................................... 25 4.程序设计.................................................................................................. 27 5.实验结果.................................................................................................. 27

五、结论......................................................................................... 31

(一)实验结论 .............................................................................................. 31

1.结论.......................................................................................................... 31 2.实验中的不足.......................................................................................... 31 3.BP网络的局限性.................................................................................... 31

(二)前景展望 .............................................................................................. 31

参考文献......................................................................................... 32 致谢 ................................................................................................. 33

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