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Application of artificial neural networks to the prediction of dust storms in Northwest China

机译:人工神经网络在西北地区沙尘暴预报中的应用

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Artificial neural networks (ANN) are non-linear mapping structures analogous to the functioning of the human brain. In this study, we take the ANN approach to model and predict the occurrence of dust storms in Northwest China, by using a combination of daily mean meteorological measurements and dust storm occurrence. The performance of the ANN model in simulating dust storm occurrences is compared with a stepwise regression model. The correlation coefficients between the observed and the estimated dust storm occurrences obtained from the neural network procedure are found to be significantly higher than those obtained from the regression model with the same input data. The prediction tests show that the ANN models used in this study have the potential of forecasting dust storm occurrence in Northwest China by using conventional meteorological variables.
机译:人工神经网络(ANN)是类似于人脑功能的非线性映射结构。在这项研究中,我们通过结合每日平均气象测量和沙尘暴的发生,采用ANN方法对西北地区沙尘暴的发生进行建模和预测。将ANN模型在模拟沙尘暴事件中的性能与逐步回归模型进行了比较。发现从神经网络程序获得的观测到的沙尘暴和估计的沙尘暴发生之间的相关系数明显高于从具有相同输入数据的回归模型获得的相关系数。预测测试表明,本研究中使用的ANN模型具有使用常规气象变量预测西北地区沙尘暴发生的潜力。

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