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首页> 外文期刊>Renewable energy >A comparison of Measure-Correlate-Predict Methodologies using LiDAR as a candidate site measurement device for the Mediterranean Island of Malta
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A comparison of Measure-Correlate-Predict Methodologies using LiDAR as a candidate site measurement device for the Mediterranean Island of Malta

机译：使用LiDAR作为马耳他地中海岛的候选站点测量设备的测量相关预测方法的比较

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This study compares various MCP methodologies in predicting wind speed and direction at various heights. The candidate site measurements were obtained by means of a Light Detection and Ranging System (LiDAR) deployed on a building on the coast in the northern part of the Mediterranean Island of Malta. MCP methodologies tested Artificial Neural Networks, Support Vector Regression and Decision Trees, apart from the traditional regression techniques. The performance of the MCP techniques was analysed by means of coefficients of determination, together with the Mean Squared Error and the Mean Absolute Error of the residuals. Conclusions reached are that the results depend on the LiDAR measurement height and on the Measure-Correlate-Predict methodology used. Another conclusion drawn from the analysis is that although some regression methodologies show a better behaviour in correlating the candidate and reference site, they might show a different behaviour when used for prediction. Hence, there is no methodology which can be classified as being the best overall, but it is best to analyse various methodologies when applying the Measure-Correlate-Predict technique. (C) 2018 Elsevier Ltd. All rights reserved.
机译：本研究比较了各种MCP方法在预测不同高度的风速和风向方面的方法。候选站点的测量是通过部署在马耳他地中海岛北部海岸的一栋建筑物上的光检测和测距系统（LiDAR）获得的。 MCP方法除了传统的回归技术外，还测试了人工神经网络，支持向量回归和决策树。通过确定系数，以及残差的均方误差和平均绝对误差，对MCP技术的性能进行了分析。得出的结论是，结果取决于LiDAR测量高度和所使用的Measure-Correlate-Predict方法。从分析中得出的另一个结论是，尽管某些回归方法在关联候选位置和参考位置方面显示出更好的行为，但是当用于预测时，它们可能显示出不同的行为。因此，没有一种方法可以被归类为最好的总体方法，但是在应用测量相关预测技术时最好分析各种方法。 （C）2018 Elsevier Ltd.保留所有权利。

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