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A pseudo-inverse method as an alternative in forecasting geothermal energy consumption and palm fruit production

机译:一种伪逆方法,作为预测地热能消耗和棕榈果生产的替代方案

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Forecasting is one among important aspects in giving an overview of future event, and even in making a decision for the respective problems to the event. Sometimes forecasting is done by correlating two different events or objects. Technically this is done by comparing data sets from these events. The most common method used to see the correlation between two data sets is the regression method or linear regression when the relationship is assumed to be linear. In this paper we discuss a different method which use pseudo-inverse of a matrix resulting from the data sets of the events. As the examples, we use the method in forecasting world geothermal energy consumption during the period of 1990-2010 and the palm fruit production in Pt. Perkebunan (PERSERO) Medan palm plantation during the period of 2011-2012. We compare the result from the linear regression method and from the pseudo-inverse method. In obtaining the pseudo-inverse of the resulting matrix we use singular value decomposition (SVD) which implemented in MATLAB program. The results show that in these different examples the linear regression method outperform the pseudo-inverse method. In the case of geothermal energy consumption, the Mean Absolute Percentage Error (MAPE) are 0.02619 for the linear regression method and 0.22107 for the pseudo-inverse method. While in the case of palm fruit production, MAPE are 0.09913 for the linear regression method and 0.10369 for the pseudo-inverse method.
机译:预测是概述未来事件概述的重要方面之一,甚至在决定事件中的各个问题方面。有时会通过关联两个不同的事件或对象来完成预测。从技术上讲,这是通过比较来自这些事件的数据集。用于看到两个数据集之间的相关的最常用方法是当假设关系线性时的回归方法或线性回归。在本文中,我们讨论了一种不同的方法,它使用由事件的数据集产生的矩阵的伪逆。作为实施例,我们在1990 - 2010年期间使用该方法预测世界地热能耗和PT的棕榈果生产。 Perkebunan(Persero)Medan Palm Plantation 2011-2012期间。我们将结果与线性回归方法和伪逆方法进行比较。在获取所得矩阵的伪逆方面,我们使用在Matlab程序中实现的奇异值分解(SVD)。结果表明,在这些不同的例子中,线性回归方法优于伪逆方法。在地热能消耗的情况下,用于线性回归方法的平均绝对百分比误差(MAPE)为0.02619,对于伪逆方法,为0.22107。虽然在棕榈果生产的情况下,MAPE为线性回归方法为0.09913,为伪反转法为0.10369。

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