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Machine learning approach for analysis and prediction of cloud particle size and shape distribution

机译:机器学习方法来分析和预测云的粒径和形状分布

摘要

Techniques for analysis and prediction of cloud particle distribution and solar radiation are provided. In one aspect, a method for analyzing cloud particle characteristics includes the steps of: (a) collecting meteorological data; (b) calculating solar radiation values using a radiative transfer model based on the meteorological data and blended guess functions of a cloud particle distribution (c) optimizing the cloud particle distribution by optimizing the weight coefficients used for the blended guess functions of the cloud particle distribution based on the solar radiation values calculated in step (b) and measured solar radiation values; (d) training a machine-learning process using the meteorological data collected in step (a) and the cloud particle distribution optimized in step (c) as training samples; and (e) predicting future solar radiation values using forecasted meteorological data and the machine-learning process trained in step (d).
机译:提供了用于分析和预测云粒子分布和太阳辐射的技术。在一个方面,一种用于分析云颗粒特征的方法包括以下步骤:(a)收集气象数据; (b)根据气象数据和云粒子分布的混合猜测函数使用辐射传递模型计算太阳辐射值(c)通过优化用于云粒子分布的混合猜测函数的权重系数来优化云粒子分布基于在步骤(b)中计算的太阳辐射值和测得的太阳辐射值; (d)使用步骤(a)中收集的气象数据和步骤(c)中优化的云粒子分布作为训练样本来训练机器学习过程; (e)使用预测的气象数据和步骤(d)中训练的机器学习过程,预测未来的太阳辐射值。

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