|本期目录/Table of Contents|

[1]葛利,印桂生.基于小波和过程神经网络的时序聚类分析[J].电机与控制学报,2011,(12):78-82.
 GE Li,YIN Gui-sheng.Time series clustering analysis based on wavelet and process neural networks[J].,2011,(12):78-82.
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基于小波和过程神经网络的时序聚类分析(PDF)
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
期数:
2011年12
页码:
78-82
栏目:
出版日期:
2011-12-20

文章信息/Info

Title:
Time series clustering analysis based on wavelet and process neural networks
作者:
葛利; 印桂生;
哈尔滨工程大学计算机科学与技术学院; 哈尔滨商业大学计算机与信息工程学院;
Author(s):
GE Li12YIN Gui-sheng1
1.College of Computer Science and Technology,Harbin Engineering University,Harbin 150001,China;2.School of Computer and Information Engineering,Harbin Commerce University,Harbin 150028,China
关键词:
时间序列 聚类分析 自组织过程神经网络 小波
Keywords:
time series clustering analysis self-organization process neural networks wavelet
分类号:
TP311.13
DOI:
-
文献标志码:
A
摘要:
针对时序背景下的聚类问题,提出一种基于小波和改进自组织过程神经网络的时序聚类方法,首先应用小波变换对原时序数据进行小波分解,在保留相关聚类特征的原则下,对信号进行重构;然后将重构信号拟合为时变函数作为过程神经网络的输入,应用改进的竞争算法训练自组织过程神经网络,利用过程神经网络输入为时变函数的特点,将经过小波处理后的时序信号特征充分考虑到聚类分析中,网络提取输入函数隐含的过程式模式特征并进行自组织,给出了改进的竞争学习算法;最后应用UCI数据集聚类结果表明,该方法在聚类正确率、网络运行时间和收敛速度上均有提高,同时在聚类质量、聚类速度方面表现出良好性能,能有效地应用于时序聚类。
Abstract:
For time series clustering problem,a method based on wavelet and improved self-organization process neural networks(PNN) was proposed.First,original time series data was decomposed by wavelet.Under the principle of reserving clustering characteristics,the signal was reconstructed.And then reconstructed signal fitted into time-varying functions was used as PNN’s input.Self-organization PNN was trained by improved competition algorithm.Making use of time-varying input characteristic of PNN,the tim...

参考文献/References:

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备注/Memo

备注/Memo:
黑龙江省科技攻关计划项目(GC05A118);哈尔滨市科技创新人才研究专项资金项目(2008RFQXG072)
更新日期/Last Update: 2012-04-16