Hybridizing Pattern Matching and Neural Network for Time Series Prediction

被引：0

作者：

Nguyen Thanh Son ^{[1
]}

Duong Tuan Anh ^{[2
]}

机构：

[1] Ho Chi Minh Univ Tech Educ, Fac Informat Technol, Ho Chi Minh City, Vietnam

[2] Ho Chi Minh Univ Technol, Fac Comp Sci & Engn, Ho Chi Minh City, Vietnam

来源：

2013 THIRD WORLD CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGIES (WICT) | 2013年

关键词：

time series; time series prediction; k-nearest-neighbors; artificial neural network; hybrid method; UNIVARIATE; MODELS;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Time series prediction is a non-trivial task for forecasters in various areas. In this paper, we introduce a new hybrid method for time series prediction. This hybrid method is a combination of k-nearest neighbors method and neural network model. The new method can take full advantage of the individual strengths of the two models to create a more effective approach for time series prediction. Experimental results show that our proposed method outperforms neural network model and k-nearest neighbors method used separately in time series prediction.

引用

页码：19 / 24

页数：6

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