Time series prediction using fuzzy wavelet neural network model

Authors:
Rahib H. Abiyev
Affiliations:
Department of Computer Engineering, Near East University, Lefkosa, North Cyprus
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Year:
2006

Citing 5
Cited 1

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Abstract

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.