Nonlinear time series prediction based on the dynamic characteristics clustering neural network

被引：1
|
作者：
Yi, Lin [1 ,2 ]
机构：
[1] Nanjing Univ Informat Sci & Technol, Coll Informat & Control, Nanjing 210044, Jiangsu, Peoples R China
[2] Jiangsu Key Lab Big Data Anal Technol, Nanjing 210044, Jiangsu, Peoples R China
来源：
PROCEEDINGS 2015 SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND ENGINEERING APPLICATIONS ISDEA 2015 | 2015年
关键词：
Neural network; Clustering; Dynamic characteristics; Time series;
D O I：
10.1109/ISDEA.2015.136
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel nonlinear time series prediction method based on the dynamic clustering neural network is proposed. This method selects prediction samples which are similar with training samples according to the cluster analysis based on the dynamic characteristics of samples and then a new subset of the samples is obtained. All of the samples in this subset have the similar dynamic characteristics. By training with these samples, a model of BP neural network based on clustering is got and it is used in nonlinear time series prediction. Take the stress data of a large span bridge tower induced by strong typhoon as example. The results indicate the validity and the better prediction accuracy of this method in nonlinear time series prediction.
引用
收藏
页码：522 / 525
页数：4
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