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초록
In this study, the volume of Pohang Port was predicted. All cargo of Pohang port, iron ore, steel, and bituminous coals were selected as prediction targets. SARIMA, Prophet, and Neural Prophet were used as analysis methods. The predictive power of each model was verified, and a predictive model with high performance was used to predict the volume of goods in Pohang port. As a result of the analysis, it was found that Neural Prophet showed the highest performance in all predictive power. As a result of predicting the future volume of goods until August 2027 using Neural Prophet, it was found that the volume of all items in Pohang port was decreasing. In particular, it was analyzed that the decline in steel cargo was steep. In order to increase the volume of cargo at Pohang port, it is necessary to diversify the cargo handled at Pohang port and check the policy of increasing the volume of cargo.
키워드
- 제목
- 시계열 데이터를 활용한 포항항 물동량 예측: SARIMA, Prophet, Neural Prophet의 적용
- 제목 (타언어)
- Throughput Prediction of Pohang Port using Time Series Data: Application of SARIMA, Prophet and Neural Prophet
- 저자
- 오진호; 최정원; 강태현; 서영준; 곽동욱
- 발행일
- 2022-12
- 유형
- Y
- 저널명
- 무역학회지
- 권
- 47
- 호
- 6
- 페이지
- 291 ~ 305
- 언어
- KOR
- 출판사
- 한국무역학회
- 발행국가
- 대한민국
- 분량
- 15 페이지
- ISSN
- P 1226-2765