Forecasting Nonlinear Chaotic Time Series with Function Expression Method Based on an Improved Genetic-Simulated Annealing Algorithm

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 geneti...

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Detalles Bibliográficos
Autores principales: Wang, Jun, Zhou, Bi-hua, Zhou, Shu-dao, Sheng, Zheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4426662/
https://www.ncbi.nlm.nih.gov/pubmed/26000011
http://dx.doi.org/10.1155/2015/341031

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4426662/
https://www.ncbi.nlm.nih.gov/pubmed/26000011
http://dx.doi.org/10.1155/2015/341031

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