International Journal of
Physical Sciences

  • Abbreviation: Int. J. Phys. Sci.
  • Language: English
  • ISSN: 1992-1950
  • DOI: 10.5897/IJPS
  • Start Year: 2006
  • Published Articles: 2569

Full Length Research Paper

Chaotic time series prediction and Mackey-Glass simulation with fuzzy logic

Yasmin Zahra Jafri1, Amir Waseem2*, Lalarukh Kamal3, S. Masood Raza4, Muhammad Sami5 and Syed Haider Shah1
  1Departments of Statistics, University of Balochistan, Quetta, Pakistan. 2Department of Bio Sciences, COMSATS Institute of Information Technology, Islamabad, Pakistan. 3Departments of Mathematics, University of Balochistan, Quetta, Pakistan. 4Department of Physics, Federal Urdu University of Arts, Science and Technology, Gulshan-e-Iqbal Campus, Karachi, Pakistan. 5Emerging Sector Wing, Ministry of Production, Islamabad, Pakistan.
Email: [email protected]

  •  Accepted: 10 April 2012
  •  Published: 30 April 2012



The present study was performed with fuzzy logic (FL) time series prediction modeling on a twenty years hourly averaged wind data, that is, 1985 to 2004 for Quetta, Pakistan. A free fuzzy logic design was followed and hourly wind data for spring prediction were obtained (February, March and April). It was found that the prediction is reliable and precise. Non-stationarity or random walk in wind data exists but it does not influence prediction. Mackey-Glass (MG) simulation of wind data indicated chaos or non periodicity in time series. Moreover, stable attractors were observed in MG-time series, in which the origin is yet unknown. The attractors seen in MG simulation do not influence FL time series prediction.


Key words: Fuzzy logic, artificial neural networks, antecedents, the adaptive neural fuzzy inference system, autoregressive integrated moving average.