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Simulating Wind Speed Data by Stochastic Markov Chain Model

机译:用随机马尔可夫链模型模拟风速数据

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In the present study the hourly wind speed data at two meteorological stations in Malaysia have been simulated by using probability transition matrices of Markov chain models. Depending upon the wind speed time series, the wind states have been selected to capture the shape of the probability density function. The manners in which Markov models can be used to generate wind speed time series are described. The models have been used to generate hourly synthetic wind speed time series. The generated time series have been examined to determine their ability to preserve the properties of the observed wind speed time series. A satisfactory accordance has been noted between the observed and the generated wind speed time series data.
机译:在本研究中,已使用马尔可夫链模型的概率转移矩阵对马来西亚两个气象站的每小时风速数据进行了模拟。根据风速时间序列,已选择风状态以捕获概率密度函数的形状。描述了马尔可夫模型可用于生成风速时间序列的方式。这些模型已用于生成每小时的合成风速时间序列。已经检查了生成的时间序列,以确定它们保留观察到的风速时间序列的属性的能力。在观测到的风速时间序列数据和生成的风速时间序列数据之间已经注意到令人满意的一致性。

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