Improvement of Propeller Hydrodynamic Prediction Model Based on Multitask ANN and Its Application in Optimization Design

Improvement of Propeller Hydrodynamic Prediction Model Based on Multitask ANN and Its Application in Optimization Design

A multitask learning (MTL) model based on artificial neural networks (ANNs) is proposed in this study to improve the prediction accuracy and physical reliability of marine propeller hydrodynamic performance. The propeller’s comprehensive geometric features are used as inputs, and the coefficients of...

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Bibliographic Details
Main Authors: Liang Li, Yihong Chen, Lu Huang, Qing Hai, Denghai Tang, Chao Wang
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Journal of Marine Science and Engineering
Subjects:
multitask learning
fast prediction
marine propeller
optimization design
open-water performance
Online Access:https://www.mdpi.com/2077-1312/13/1/183
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