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Taking electrical signals in Dendranthema morifolium as time series and using model analysis of the autoregressive integrated moving average (ARIMA), an intelligent forecasting system was constructed to forecast plant characters. It was less than 13% at relative errors between the real and forecast values at backward 10 points of signals, which shows it is feasible to forecast the plant signal for...
Taking electrical signals in the scindpus aureus as the time series and using the Gaussian radial base function (RBF) and a delayed input window chosen at 50, an intelligent RBF forecast system is set up to forecast signals by the wavelet soft-threshold de-noised backward. It is obvious that the electrical signal in S. aureus is a sort of weak, unstable and low frequency signals. There is the maximum...
Taking electrical signals in the Catharanthus roseus as the time series and using the Gaussian radial base function (RBF) and a delayed input window chosen at 50, an intelligent RBF forecast system is set up to forecast signals by the wavelet soft-threshold de-noised backward. It is obvious that the electrical signal in Catharanthus roseus is a sort of weak, unstable and low frequency signals. There...
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