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Part A: Innovative Data Augmentation Approach to Enhance Machine Learning Efficiency—Case Study for Hydrodynamic Purposes

These days, AI and machine learning (ML) have become pervasive in numerous fields. However, the maritime industry has faced challenges due to the dynamic and unstructured nature of environmental inputs. Hydrodynamic models, vital for predicting ship responses and estimating sea states, rely on diver...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Hamed Majidiyan, Hossein Enshaei, Damon Howe, Eric Gubesch
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2024-12-01
Schriftenreihe:Applied Sciences
Schlagworte:
machine learning
AI
seakeeping
data analysis
numerical modelling
feature engineering
Online-Zugang:https://www.mdpi.com/2076-3417/15/1/158
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