The Journal of the Convergence on Culture Technology (문화기술의 융합)

The International Promotion Agency of Culture Technology (국제문화기술진흥원)
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International Diesel Price Prediction Model based on Machine Learning with Global Economic Indicators

세계 경제 지표를 활용한 머신러닝 기반 국제 경유 가격 예측 모델 개발

  • 최아린 (서울여자대학교 데이터사이언스전공) ;
  • 박민서 (서울여자대학교 데이터사이언스학과)
  • Received : 2023.10.03
  • Accepted : 2023.11.05
  • Published : 2023.11.30
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Abstract

International diesel prices play a crucial role in various sectors such as industry, transportation, and energy production, exerting a significant impact on the global economy and international trade. In particular, an increase in international diesel prices can burden consumers and potentially lead to inflation. However, previous studies have primarily focused on gasoline. Therefore, this study aims to propose an international diesel price prediction model. To achieve this goal, we utilize various global economic indicators and train a linear regression model, which is one of the machine learning methodologies. This model clearly identifies the relationship between global economic indicators and international diesel prices while providing highly accurate predictions. It is expected to aid in understanding overall economic trends including market changes.

국제 경유 가격은 산업, 교통 및 에너지 생산과 같은 여러 분야에서 중요한 역할을 수행하며, 세계 경제와 국제 무역에도 큰 영향을 미친다. 특히, 국제 경유 가격의 상승은 소비자에게 부담을 주고 인플레이션의 원인이 될 수있다. 그러나 기존 연구들은 주로 휘발유에 초점을 맞추어 진행되었다. 따라서 본 연구는 국제 경유 가격 예측 모델을 제안하고자 한다. 이를 위해 다양한 세계 경제 지표들을 활용하여 머신러닝 방법론 중 하나인 선형 회귀 모델로 학습한다. 해당 모델은 세계 경제 지표들과 국제 경유 가격 간의 관계를 명확하게 파악함과 동시에 높은 정확도로 예측한다. 이는 시장 변화를 비롯한 전반적인 경제 흐름 파악에 도움이 될 것으로 기대된다.

Keywords

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