In this paper, we develop a function of population, GDP, import, and export by applying a hybrid bat algorithm (BAT) and artificial neural network (ANN). We apply these methods to forecast oil consumption in Iran. For this purpose, an improved artificial neural network (ANN) structure, which is optimized by the BAT is proposed. The variables between 1980 and 2017 were used, partly for installing and testing the method. This method would be helpful in forecasting oil consumption and would provide a level playing field for checking the energy policy authority impacts on the structure of the energy sector in an economy such as Iran with high economic interventionism by the government. The result of the model shows that the findings are in close agreement with the observed data, and the performance of the method was excellent. We demonstrate that its efficiency could be a helpful and reliable tool for monitoring oil consumption.

中文翻译：

---

基于BAT算法的人工神经网络混合预测伊朗石油消费的新方法。

在本文中，我们通过应用混合蝙蝠算法（BAT）和人工神经网络（ANN）开发了人口，GDP，进出口的函数。我们将这些方法应用于预测伊朗的石油消耗。为此，提出了一种通过BAT优化的改进的人工神经网络（ANN）结构。使用1980年至2017年之间的变量，部分用于安装和测试该方法。这种方法将有助于预测石油消耗量，并为检查能源政策权威机构对伊朗等经济高度受政府干预的经济体中能源部门结构的影响提供一个公平的竞争环境。该模型的结果表明，所发现的结果与观察到的数据非常吻合，该方法的性能非常好。