Chaotic time series prediction by artificial neural networks

Article type: Research Article

Authors: Rafsanjani, Marjan Kuchaki^* | Samareh, Meysam

Affiliations: Department of Computer Science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran

Correspondence: [*] Corresponding author: Marjan Kuchaki Rafsanjani, Department of Computer Science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran. E-mail:kuchaki@uk.ac.ir

Abstract: In this paper, we used four types of artificial neural network (ANN) to predict the behavior of chaotic time series. Each neural network that used in this paper acts as global model to predict the future behavior of time series. Prediction process is based on embedding theorem and time delay determined by this theorem. This ANN applied to the time series that generated by Mackey-glass equation that has a chaotic behavior. At the end, all neural networks are used to solve this problem and their results are compared and analyzed.

Keywords: Artificial neural network (ANN), chaotic systems, Mackey-glass (MG), prediction, time series

DOI: 10.3233/JCM-160643

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 16, no. 3, pp. 599-615, 2016