Electricity is a critical utility for social growth. Accurate estimation of its consumption plays a vital role in economic development. A database that included past electricity consumption data from all OECD countries was prepared. Since national trends may be transferable from one country to another, the entire database was modeled and simulated via machine learning techniques to forecast the energy consumption of each country. Understanding similarities among the profiles of different countries could increase predictive accuracy and improve associated public policies.

中文翻译：

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预测OECD国家的用电量：全球机器学习建模方法

电力是社会发展的重要工具。准确估计其消费量对经济发展起着至关重要的作用。准备了一个数据库，其中包括来自所有经合组织国家的过去用电量数据。由于国家趋势可以从一个国家转移到另一个国家，因此整个数据库通过机器学习技术进行建模和仿真，以预测每个国家的能源消耗。理解不同国家的概况之间的相似性可以提高预测的准确性并改善相关的公共政策。