Mackey-glass chaotic time series prediction using modified rbf neural networks

Akhmad Faqih, Aldo Pratama Lianto, Benyamin Kusumoputro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The characteristics of a nonlinear dynamical system within chaotic system is more intensely studied recently, due to many real-world applications of the nonlinear chaotic system are increasing. For characterizing the ordinary system, usually the relationship between the linearity and the nonlinearity of parameters in the system is needed to be firstly derived, however, creating the mathematical model of the real chaotic system is still a problematic since insufficient basic physical phenomena should be analyzed. Hence, artificial neural networks approach that performed based on nonlinear mathematical model is quite adequate to be used to analyze the chaotic phenomena within the system. Solving the multi-step ahead prediction problem of time series chaotic system is one of the top challenging issues, especially on how to obtain a higher prediction rate. In this paper, a modified Radial Basis Function Neural Network (RBF-NN) is developed and be tested for predicting the future state of a Mackey-Glass equation as the chaotic system. Results experiments show that using training testing paradigm of 50%:50%, the calculated of confidence level accuracy of the neural-predictor system is satisfied for up to 30-steps ahead prediction.

Original languageEnglish
Title of host publicationProceedings of the 2019 2nd International Conference on Software Engineering and Information Management, ICSIM 2019 - Workshop 2019 2nd International Conference on Big Data and Smart Computing, ICBDSC 2019
PublisherAssociation for Computing Machinery
Pages7-11
Number of pages5
ISBN (Electronic)9781450366427
DOIs
Publication statusPublished - 10 Jan 2019
Event2nd International Conference on Software Engineering and Information Management, ICSIM 2019 - and its Workshop 2019 2nd International Conference on Big Data and Smart Computing, ICBDSC 2019 - Bali, Indonesia
Duration: 10 Jan 201913 Jan 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2nd International Conference on Software Engineering and Information Management, ICSIM 2019 - and its Workshop 2019 2nd International Conference on Big Data and Smart Computing, ICBDSC 2019
CountryIndonesia
CityBali
Period10/01/1913/01/19

Keywords

  • Chaotic system
  • Mackey-glass equation
  • Multi-step ahead prediction
  • Radial basis function
  • Self-organized maps

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  • Cite this

    Faqih, A., Lianto, A. P., & Kusumoputro, B. (2019). Mackey-glass chaotic time series prediction using modified rbf neural networks. In Proceedings of the 2019 2nd International Conference on Software Engineering and Information Management, ICSIM 2019 - Workshop 2019 2nd International Conference on Big Data and Smart Computing, ICBDSC 2019 (pp. 7-11). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3305160.3305187