NEURAL NETWORK BP MODEL APPROXIMATION AND PREDICTION OF COMPLICATED WEATHER SYSTEMS*

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  • Abstract

    An artificial neural network BP model and its revised algorithm are used to approximate quite successfully a Lorenz chaotic dynamic system and the mapping relation is established between the indices of Southern Oscillation and equatorial zonal wind and lagged equatorial eastern Pacific sea surface temperature(SST) in the context of NCEP/NCAR data,and thereby a model is prepared.The constructed net model shows fairly high fit precision and feasible prediction accuracy,thus making itself of some usefulness to the prognosis of intricate weather systems.
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ZHANG Ren, YU Zhihao, JIANG Quanrong. 2001: NEURAL NETWORK BP MODEL APPROXIMATION AND PREDICTION OF COMPLICATED WEATHER SYSTEMS*. Journal of Meteorological Research, 15(1): 105-115.
ZHANG Ren, YU Zhihao, JIANG Quanrong. 2001: NEURAL NETWORK BP MODEL APPROXIMATION AND PREDICTION OF COMPLICATED WEATHER SYSTEMS*. Journal of Meteorological Research, 15(1): 105-115.
shu
ZHANG Ren, YU Zhihao, JIANG Quanrong. 2001: NEURAL NETWORK BP MODEL APPROXIMATION AND PREDICTION OF COMPLICATED WEATHER SYSTEMS*. Journal of Meteorological Research, 15(1): 105-115.
ZHANG Ren, YU Zhihao, JIANG Quanrong. 2001: NEURAL NETWORK BP MODEL APPROXIMATION AND PREDICTION OF COMPLICATED WEATHER SYSTEMS*. Journal of Meteorological Research, 15(1): 105-115.
shu
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