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Forecasting electricity consumption of OECD countries: A global machine learning modeling approach

机译:预测经合组织国家的电力消费:全球机器学习建模方法

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摘要

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.
机译:电力是社会增长的关键效用。 准确估计其消费在经济发展中起着至关重要的作用。 准备了一个包含所有经合组织国家的电力消费数据的数据库。 由于国家趋势可能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模拟,以预测每个国家的能源消耗。 了解不同国家的简档之间的相似性可以提高预测准确性和改善相关的公共政策。

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