Forecasting the annual electricity consumption of Turkey using a hybrid model

Gokhan Aydogdu, O. Yıldız
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引用次数: 5

Abstract

In this study, we implemented traditional, artificial intelligence and hybrid methods to predict electricity consumption of Turkey. While traditional method is multiple linear regression and artificial intelligence method is artificial neural network, hybrid method is a new method combining these two methods. The data used in the study was provided from Turkish Electricity Transmission Company, Turkish Electricity Distribution Company, Ministry of Energy and Natural Resources and Turkish Statistical Institute which are the public institutions in Turkey. The performance was evaluated using mean absolute percentage error (MAPE), mean square error (MSE) and root mean square error (RMSE). The test of the proposed hybrid model resulted in an average absolute forecast error of 2.25 percent.
使用混合模型预测土耳其的年用电量
在本研究中,我们实施了传统、人工智能和混合方法来预测土耳其的用电量。传统方法是多元线性回归,人工智能方法是人工神经网络,而混合方法是将这两种方法结合起来的一种新方法。研究中使用的数据由土耳其的公共机构土耳其输电公司、土耳其配电公司、能源和自然资源部和土耳其统计研究所提供。使用平均绝对百分比误差(MAPE)、均方误差(MSE)和均方根误差(RMSE)对性能进行评估。对混合模型的测试结果表明,该模型的平均绝对预测误差为2.25%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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