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Spatio-temporal Kriging of Lower Caribbean Wind Data 下加勒比海风资料的时空克里格
Pub Date : 2021-07-01 DOI: 10.47412/zasa8968
N. Ramsamooj
Planning of a wind farm location requires significant data. However, wind speed data sets in the lower Caribbean are usually incomplete. This paper considers imputation by spatio-temporal kriging using data from neighbouring locations. Temporal basis functions with spatial covariates are used to model diurnal wind speed cyclicity. The residual set of our spatio-temporal model is modelled as a Gaussian spatial random field. Fitted models may be used for spatial prediction as well as imputation. Examples of predictions are illustrated using two months of hourly data from eight Caribbean locations with prediction accuracy being assessed by cross validation and residuals.
规划风电场的位置需要大量的数据。然而,加勒比海下游地区的风速数据集通常是不完整的。本文考虑利用邻近位置的数据进行时空克里格插值。采用带空间协变量的时间基函数来模拟日风速周期。我们的时空模型的残差集被建模为高斯空间随机场。拟合模型既可用于空间预测,也可用于估算。使用来自八个加勒比地点的两个月的每小时数据说明了预测的例子,并通过交叉验证和残差评估了预测的准确性。
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West Indian Journal of Engineering
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