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Application of neural network model to Guangxi ensemble precipitation prediction

机译:神经网络模型在广西集合降水预报中的应用

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摘要

Using the method of artificial neural networks and principal component analysis (PCA) to study on a variety of numerical forecast products for the same precipitation forecast. The results showed that the fitting accuracy of the principal component analysis artificial neural network ensemble model is better than each sub-product and the experimental results of the independent samples also shows its better prediction accuracy and stability. The model is a good prospects for business applications.
机译:使用人工神经网络和主成分分析(PCA)方法研究同一降水量预报的各种数值预报产品。结果表明,主成分分析人工神经网络集成模型的拟合精度优于各子产品,独立样本的实验结果也显示出较好的预测精度和稳定性。该模型是业务应用程序的良好前景。

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