통계적 접근 방법을 이용한 저속비대선 및 컨테이너선의 동력 성능 추정Powering Performance Prediction of Low-Speed Full Ships and Container Carriers Using Statistical Approach
- Other Titles
- Powering Performance Prediction of Low-Speed Full Ships and Container Carriers Using Statistical Approach
- Authors
- 김유철; 김건도; 김명수; 황승현; 김광수; 연성모; 이영연
- Issue Date
- 8월-2021
- Publisher
- 대한조선학회
- Keywords
- Power prediction(동력 예측); Linear regression(선형 회귀); Machine learning(기계 학습); Hull form variables(선형 변수); Fullship(저속비대선); Container carrier(컨테이너선)
- Citation
- 대한조선학회 논문집, v.58, no.4, pp 234 - 242
- Pages
- 9
- Journal Title
- 대한조선학회 논문집
- Volume
- 58
- Number
- 4
- Start Page
- 234
- End Page
- 242
- URI
- https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/9639
- DOI
- 10.3744/SNAK.2021.58.4.234
- ISSN
- 1225-1143
- Abstract
- In this study, we introduce the prediction of brake power for low-speed full ships and container carriers using the linear regression and a machine learning approach. The residual resistance coefficient, wake fraction coefficient, and thrust deduction factor are predicted by regression models using the main dimensions of ship and propeller. The brake power of a ship can be calculated by these coefficients according to the 1978 ITTC performance prediction method. The mean absolute error of the predicted power was under 7%. As a result of several validation cases, it was confirmed that the machine learning model showed slightly better results than linear regression.
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