Abstract
AbstractThe development of a fuzzy wavelet neural network (FWNN) for the prediction of electricity consumption is presented. The fuzzy rules that contain wavelets are constructed. Based on these rules, the structure of FWNN-based system is described. The FWNN system is applied for modeling and prediction of complex time series. The gradient algorithm and genetic algorithm are used for learning of FWNN parameters. The developed FWNN is applied for prediction of electricity consumption. This process has high-order nonlinearity. The statistical data for the last 10 years are used for the development of FWNN prediction model. The effectiveness of the proposed system is evaluated with the results obtained from the simulation of FWNN-based prediction system and with the comparative simulation results of previous related models.
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