NDLI: Time series prediction using pattern matching

Content Provider	IEEE Xplore Digital Library
Author	Nguyen Thanh Son Nguyen Hoai Le Duong Tuan Anh
Copyright Year	2013
Description	Author affiliation: Fac. of Inf. Technol., HCM City Univ. of Tech. Educ., Ho Chi Minh City, Vietnam (Nguyen Thanh Son; Nguyen Hoai Le) \|\| Fac. of Comput. Sci. & Eng., HCM City Univ. of Technol. HCM City, Ho Chi Minh City, Vietnam (Duong Tuan Anh)
Abstract	Time series forecasting is very important in several domains and has received a lot of interest from researchers in recent years. In this paper, we investigate the use of pattern matching technique in seasonal or trend time series prediction. First, this technique retrieves the sequence prior to the interval to be forecasted. Then this sequence is used as a sample for searching k-nearest neighbors or neighbors within a threshold T in historical data. Next, sequences next to these found patterns are retrieved. Finally, the forecasted sequence is calculated by averaging the sequences found in the immediate previous step. The experimental results showed that this approach produces competitive results on seasonal or trend time series in comparison to artificial neural network (ANN) in terms of prediction accuracy and time efficiency. In our experiment, we also examine the impact of parameter values k and T on the predictive accuracy.
Sponsorship	IEEE Vietnam Sect.
Starting Page	401
Ending Page	406
File Size	487203
Page Count	6
File Format	PDF
ISBN	9781467320870
e-ISBN	9781467320887
DOI	10.1109/ComManTel.2013.6482428
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-21
Publisher Place	Vietnam
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy MP_C Time series analysis Artificial neural networks Time series Time series prediction Rivers Indexes Forecasting Skyline Index Pattern matching
Content Type	Text
Resource Type	Article

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