WAVELET DECOMPOSITION AND COMPOSITIVE PREDICTION ON THE MODALITY INDEX OF THE WESTPACIFIC SUBTROPICAL HIGH
Received date: 2003-04-09
Revised date: 2003-08-29
Online published: 2004-08-01
Based on the method of associating wavelet decomposition with adaptive neurofuzzy inference system (ANFIS), a compositive prediction model on the modality index of the westPacific subtropical high(WPSH) on the monthlyseasonal scale was established. Signals can be freely extended/shrinked in frequency time domain and any passband and passlow frequency branch can be accurately produced and reconstructed by means of wavelet decomposition. Therefore, the complex WPSH modality index time series signals can be separated into several relative simple bandpass signals, which both simplify the system structure and stand out the chief characters of signals. Subsequently, the independent prediction model of the decomposed signals were established based on the advantages of ANFIS model, such as nonlinear, bearingerror, selfadapting and associationlearning and the independent predicted results were integrated finally. The test results showed that under the premise of keeping the main characters of forecast body, the prediction difficulty on WPSH system had effectively been decreased, the precision and durative of the compositive prediction model were evidently improved and promoted compared with that of traditional prediction technique.
DONG Zhao-jun , HE Jin-hai , CHEN Yi-de , ZHANG Ren . WAVELET DECOMPOSITION AND COMPOSITIVE PREDICTION ON THE MODALITY INDEX OF THE WESTPACIFIC SUBTROPICAL HIGH[J]. Advances in Earth Science, 2004 , 19(4) : 572 -578 . DOI: 10.11867/j.issn.1001-8166.2004.04.0572
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