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Study on variation in wet and low water of precipitation prediction based on Markov with weights theory

机译:基于Markov与权重理论的降水预测湿法预测变化研究

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摘要

The Markov prediction has been widely applied to simulate natural disasters in recent years as one of the modern prediction theories. This paper first uses Markov chain prediction to study the variation in wet and low water of annual precipitation. The prediction model is set up based on the rainfall data of Xianyang city from 1959 to 2006 and finally, the meteorological drought state of XIY city in 2007 and 2008 is analyzed. The results indicate that the prediction model has more satisfactory fitting accuracy, which could be applied in practical production activities.
机译:马尔可夫预测已被广泛应用于近年来模拟自然灾害作为现代预测理论之一。本文首先使用马尔可夫链预测来研究潮湿和低水水的变化。预测模型是根据咸阳市从1959年到2006年的降雨数据建立的,最后,分析了2007年和2008年的XIY城市气象干旱状态。结果表明,预测模型具有更令人满意的拟合精度,可应用于实际生产活动。

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