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中国物理学会期刊

旱涝预测的演化建模方法

CSTR: 32037.14.aps.61.119201

Evolutionary modeling for dryness and wetness prediction

CSTR: 32037.14.aps.61.119201
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  • 发展了一种旱涝预测的演化建模方法, 数值试验结果表明, 该方法能够从历史资料中准确地挖掘出气候要素演化的主要动力学特征, 所建立的模型不仅能够较好地模拟要素的历史演变情况, 而且还能够对未来的演变趋势进行准确的预测. 对于演化建模所得到的误差较大的模型, 对其预测误差序列进行二次演化建模可明显提高模型的预测精度.

     

    A new method of predicting dryness and wetness based on evolutionary modeling (EM) is presented in this paper. Numerical tests indicate that the basic dynamic characteriscs can be captured by EM and the model obtained by EM is not only able to preferablely simulate historical evolution, but also can exactly predict the future evolutionary trend of a time series. For the model obtained by EM with relatively larger prediction errors, the secondary EM can improve the prediction accuracy obviously.

     

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