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Forecasting Iran's Energy Demand Using Cuckoo Optimization Algorithm

机译：使用Cuckoo优化算法预测伊朗的能源需求

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摘要

This study deals with the modeling of the energy consumption in Iran to forecast future projections based on socioeconomic and demographic variables (GDP, population, import and export amounts, and employment) using the cuckoo optimization algorithm. For this purpose, four diverse models including different indicators were used in the analyses. Linear and power forms of equations are developed for each model. The related data between 1972 and 2013 were used, partly for installing the models. The result of the models shows that the obtained demand estimation linear models are in closer agreement with the observed data, particularly the linear model with five independent variables including GDP, population, import, export, and employment, which outperformed other linear models. Finally, the future energy demand of Iran is forecasted up to the year 2030 using these models under three scenarios.
机译：本研究涉及使用Cuckoo优化算法的社会经济和人口统计变量（GDP，人口，进出口金额和就业）来预测未来预测的伊朗能源消耗的建模。为此目的，在分析中使用包括不同指标的四种不同的模型。为每个模型开发了方程的线性和功率形式。部分用于安装模型的1972和2013之间的相关数据。模型的结果表明，所获得的需求估计线性模型与观察到的数据仔细一致，特别是具有五个独立变量的线性模型，包括GDP，人口，导出，出口和就业，其表现优于其他线性模型。最后，在三种情况下，使用这些模型预测了伊朗的未来能源需求。

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