Time Series Prediction Using Fuzzy Wavelet Neural Network Model

  • Rahib H. Abiyev
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4132)


The fuzzy wavelet neural network (FWNN) for time series prediction is presented in this paper. Using wavelets the fuzzy rules are constructed. The gradient algorithm is applied for learning parameters of fuzzy system. The application of FWNN for modelling and prediction of complex time series and prediction of electricity consumption is considered. Results of simulation of FWNN based prediction system is compared with the simulation results of other methodologies used for prediction. Simulation results demonstrate that FWNN based system can effectively learn complex nonlinear processes and has better performance than other models.


Root Mean Square Error Membership Function Fuzzy Rule Hide Neuron Electricity Consumption 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Rahib H. Abiyev
    • 1
  1. 1.Department of Computer EngineeringNear East UniversityLefkosaNorth Cyprus

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