Journal of the Society of Naval Architects of Korea (대한조선학회논문집)

The Society of Naval Architects of Korea (대한조선학회)
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A Study on the Prediction of Major Prices in the Shipbuilding Industry Using Time Series Analysis Model

시계열 분석 모델을 이용한 조선 산업 주요물가의 예측에 관한 연구

  • Ham, Juh-Hyeok (School of Smart Mobility Engineering, Halla University)
  • 함주혁 (한라대학교 스마트모빌리티공학부)
  • Received : 2021.06.10
  • Accepted : 2021.07.28
  • Published : 2021.10.20
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Abstract

Oil and steel prices, which are major pricescosts in the shipbuilding industry, were predicted. Firstly, the error of the moving average line (N=3-5) was examined, and in all three error analyses, the moving average line (N=3) was small. Secondly, in the linear prediction of data through existing theory, oil prices rise slightly, and steel prices rise sharply, but in reality, linear prediction using existing data was not satisfactory. Thirdly, we identified the limitations of linear prediction methods and confirmed that oil and steel price prediction was somewhat similar to actual moving average line prediction methods. Due to the high volatility of major price flows, large errors were inevitable in the forecast section. Through the time series analysis method at the end of this paper, we were able to achieve not bad results in all analysis items relative to artificial intelligence (Prophet). Predictive data through predictive analysis using eight predictive models are expected to serve as a good research foundation for developing unique tools or establishing evaluation systems in the future. This study compares the basic settings of artificial intelligence programs with the results of core price prediction in the shipbuilding industry through time series prediction theory, and further studies the various hyper-parameters and event effects of Prophet in the future, leaving room for improvement of predictability.

Keywords

Acknowledgement

이 연구는 논문발행일 기준으로 2021학년도 한라대학교 자율형 학술연구비의 지원에 의해 연구되었기에 이에 관련한 관계자 여러분께 감사드립니다.

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