Computer Science ›› 2013, Vol. 40 ›› Issue (Z6): 243-246.

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Prediction of Periodic Weighting Based on Optimized Functional Networks

CUI Tie-jun and MA Yun-dong   

  • Online:2018-11-16 Published:2018-11-16

Abstract: In order to improve the prediction the periodic weighting load,this paper proposed a new periodic weighting prediction method based on Functional networks(FN) optimized wavelet analysis and chaos.In the method,selected sample set data is decomposed using wavelet decomposition technique to obtain the different frequency components.The phase space of the components is reconstructed by chaos theory.The reconstructed components are respectively transmitted into FN model to carry on prediction.Finally,all the predicted components got by FN models are reconstructed by wavelet to get complete prediction waveform.The result of the calculation in the reconstruction shows that in a certain period,the load temporal sequence has some chaotic property.Through the comparison between the result of the method and three other models,the final load ware of the method is higher accuracy and convergence,but the cost of time is large.

Key words: Prediction of periodic weighting,Wavelet analysis,Chaos,Functional networks

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