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The fuzzy system with network structure as the forecasting model, and the improved genetic algorithm is taken to confirm system parameters. A case study of load forecasting in a certain power network shows that the model which is based on this way has a better fitting precision.
Different forecasting methods can lead to very different results in power system load forecast, in order to improve forecasting accuracy, a nonlinear combined forecasting method based on fuzzy adaptive variable weight is introduced. Not only the nonlinearity of electric load forecasting is considered, but also the advantage of variable weight combined forecasting is also utilized. The determination...
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