Forecasting Nonlinear Chaotic Time Series with Function Expression Method Based on an Improved Genetic-Simulated Annealing Algorithm
Joint Authors
Wang, Jun
Zhou, Shudao
Sheng, Zheng
Zhou, Bihua
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-27
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The paper proposes a novel function expression method to forecast chaotic time series, using an improved genetic-simulated annealing (IGSA) algorithm to establish the optimum function expression that describes the behavior of time series.
In order to deal with the weakness associated with the genetic algorithm, the proposed algorithm incorporates the simulated annealing operation which has the strong local search ability into the genetic algorithm to enhance the performance of optimization; besides, the fitness function and genetic operators are also improved.
Finally, the method is applied to the chaotic time series of Quadratic and Rossler maps for validation.
The effect of noise in the chaotic time series is also studied numerically.
The numerical results verify that the method can forecast chaotic time series with high precision and effectiveness, and the forecasting precision with certain noise is also satisfactory.
It can be concluded that the IGSA algorithm is energy-efficient and superior.
American Psychological Association (APA)
Wang, Jun& Zhou, Bihua& Zhou, Shudao& Sheng, Zheng. 2015. Forecasting Nonlinear Chaotic Time Series with Function Expression Method Based on an Improved Genetic-Simulated Annealing Algorithm. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1057683
Modern Language Association (MLA)
Wang, Jun…[et al.]. Forecasting Nonlinear Chaotic Time Series with Function Expression Method Based on an Improved Genetic-Simulated Annealing Algorithm. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1057683
American Medical Association (AMA)
Wang, Jun& Zhou, Bihua& Zhou, Shudao& Sheng, Zheng. Forecasting Nonlinear Chaotic Time Series with Function Expression Method Based on an Improved Genetic-Simulated Annealing Algorithm. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1057683
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057683