한국해양대학교

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Comparison of mooring system optimization using ANN based GA & Bayesian optimization

Title
Comparison of mooring system optimization using ANN based GA & Bayesian optimization
Alternative Title
ANN기반의 GA와 Bayesian 최적화 기법을 사용한 계류시스템 최적화 비교
Author(s)
LIM JISU
Keyword
Mooring systemANN(Artificial Neural Network)GA(Genetic Algorithm)Bayesian optimization
Issued Date
2022
Publisher
한국해양대학교 대학원
URI
http://repository.kmou.ac.kr/handle/2014.oak/12852
http://kmou.dcollection.net/common/orgView/200000603087
Abstract
Since a mooring system design is designed by selecting many design parameters and considering various factors, a basic design is mainly done empirically. In this basic design process, studies have been conducted to improve mooring design using static analysis results as objective cost. Static analysis cannot capture all the effects of time domain analysis. In this study, among the mooring parameters in a specific environment condition, parameters that have a large influence on the tension on the line were selected and mooring system optimization was performed using bayesian optimization & ANN based GA that use line tension result in time domain as objective cost. In conclusion, both methods of the mooring system optimization suggested a mooring system with a tension that is 50% lower than the stability criterion for line breaking. In addition, when the two optimization methods were applied to the mooring system, the advantages and disadvantages of each optimization method were confirmed.
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