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A Novel Time Series Prediction Approach Based on a Hybridization of Least Squares Support Vector Regression and Swarm Intelligence
Joint Authors
Pham, Anh-Duc
Cao, Minh-Tu
Hoang, Nhat-Duc
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-11-09
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
This research aims at establishing a novel hybrid artificial intelligence (AI) approach, named as firefly-tuned least squares supportvector regression for time series prediction ( F L S V R T S P ) .
The proposed model utilizes the least squares support vector regression (LS-SVR) as a supervised learning technique to generalize the mapping function between input and output of time series data.
In order to optimize the LS-SVR’s tuning parameters, the F L S V R T S P incorporates the firefly algorithm (FA) as the search engine.
Consequently, the newly construction model can learn from historical data and carry out prediction autonomously without any prior knowledge in parameter setting.
Experimental results and comparison have demonstrated that the F L S V R T S P has achieved a significant improvement in forecasting accuracy when predicting both artificial and real-world time series data.
Hence, the proposed hybrid approach is a promising alternative for assisting decision-makers to better cope with time series prediction.
American Psychological Association (APA)
Hoang, Nhat-Duc& Pham, Anh-Duc& Cao, Minh-Tu. 2014. A Novel Time Series Prediction Approach Based on a Hybridization of Least Squares Support Vector Regression and Swarm Intelligence. Applied Computational Intelligence and Soft Computing،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1034166
Modern Language Association (MLA)
Hoang, Nhat-Duc…[et al.]. A Novel Time Series Prediction Approach Based on a Hybridization of Least Squares Support Vector Regression and Swarm Intelligence. Applied Computational Intelligence and Soft Computing No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1034166
American Medical Association (AMA)
Hoang, Nhat-Duc& Pham, Anh-Duc& Cao, Minh-Tu. A Novel Time Series Prediction Approach Based on a Hybridization of Least Squares Support Vector Regression and Swarm Intelligence. Applied Computational Intelligence and Soft Computing. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1034166
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1034166