본문 바로가기 주메뉴 바로가기
22대 대한민국 국회 국회정보길라잡이 국회의원검색
회원가입 로그인
HOME

정보검색

소장정보 검색

국회도서관 홈으로 정보검색 소장정보 검색
결과 내 검색 동의어 포함
결과 내 검색 동의어 포함

-

초록보기

Waves are a complex phenomenon in marine and coastal areas, and accurate wave prediction is essential for the safety and resource management of ships at sea. In this study, three types of machine learning techniques specialized in nonlinear data processing were used to predict the waves of Korea waters. An optimized algorithm for each area is presented for performance evaluation and comparison. The optimal parameters were determined by varying the window size, and the performance was evaluated by comparing the mean absolute error (MAE). All the models showed good results when the window size was 4 or 7 d, with the gated recurrent unit (GRU) performing well in all waters. The MAE results were within 0.161 m to 0.051 m for significant wave heights and 0.491 s to 0.272 s for periods. In addition, the GRU showed higher prediction accuracy for certain data with waves greater than 3 m or 8 s, which is likely due to the number of training parameters. When conducting marine and offshore research at new locations, the results presented in this study can help ensure safety and improve work efficiency. If additional wave-related data are obtained, more accurate wave predictions will be possible.

권호기사

권호기사 목록 테이블로 기사명, 저자명, 페이지, 원문, 기사목차 순으로 되어있습니다.
기사명 저자명 페이지 원문 목차
Numerical investigation of motion response of the tanker at varying vertical center of gravities Van Thuan Mai, Thi Loan Mai, Hyeon Kyu Yoon p. 1-9

Crabbing motion testing of waterjet-powered ships using stern thrusters Joopil Lee, Seung-Ho Ham p. 10-17

Comparison of wave prediction and performance evaluation in Korea waters based on machine learning Heung Jin Park, Youn Joung Kang p. 18-29

Penetration behavior of jack-up leg with spudcan for offshore wind turbine to multi-layered soils using centrifuge tests Min Jy Lee, Yun Wook Choo p. 30-42

참고문헌 (20건) : 자료제공( 네이버학술정보 )

참고문헌 목록에 대한 테이블로 번호, 참고문헌, 국회도서관 소장유무로 구성되어 있습니다.
번호 참고문헌 국회도서관 소장유무
1 U.S. Army Corps of Engineers, Coastal Engineering Manual (CEM), Engineer Manual 1110-2-1100 미소장
2 Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling 미소장
3 Topographic Rossby waves in a rough-bottomed ocean 미소장
4 A shallow water intercomparison of three numerical wave prediction models (Swim) 미소장
5 Prediction of wave height and period for a constant wind velocity using the JONSWAP results 미소장
6 Long Short-Term Memory 미소장
7 Learning to Forget: Continual Prediction with LSTM 미소장
8 A novel method for long-term time series analysis of significant wave height 미소장
9 Offshore Aquaculture: I Know It When I See It 미소장
10 Ocean wave height prediction using ensemble of Extreme Learning Machine 미소장
11 Wind Wave Prediction by using Autoregressive Integrated Moving Average model : Case Study in Jakarta Bay 미소장
12 Forecasting Significant Wave Height using RNN-LSTM Models 미소장
13 Predicting Lake Erie wave heights and periods using XGBoost and LSTM 미소장
14 Machine learning advances for time series forecasting 미소장
15 Optimization of SWAN Wave Model to Improve the Accuracy of Winter Storm Wave Prediction in the East Sea 미소장
16 Prediction of Significant Wave Height in Korea Strait Using Machine Learning 미소장
17 Wave data prediction with optimized machine learning and deep learning techniques 미소장
18 STG-OceanWaveNet: Spatio-temporal geographic information guided ocean wave prediction network 미소장
19 A deep learning approach to predict significant wave height using long short-term memory 미소장
20 Research on Wind Waves Characteristics by Comparison of Regional Wind Wave Prediction System and Ocean Buoy Data 미소장

추천서가 (다양한 추천 자료를 만나보세요)

권호기사보기

권호기사 목록 테이블로 기사명, 저자명, 페이지, 원문, 기사목차 순으로 되어있습니다.
기사명 저자명 페이지 원문 기사목차