Additional study of failure behavior for ship propeller: The comparative analysis of life evaluation approaches between BP neural network, LSTM and TV-HSMM-Reference-Cited by-同舟云学术

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Additional study of failure behavior for ship propeller: The comparative analysis of life evaluation approaches between BP neural network, LSTM and TV-HSMM

Published:2024-09 Issue: Volume:307 Page:118154
ISSN:0029-8018
Container-title:Ocean Engineering
language:en
Short-container-title:Ocean Engineering

Author:

Wang Jinlong,Gao Sibo,Bao Yongjie^ORCID,Shi Zeyu,Ji Xiukun

Publisher

Elsevier BV

Reference22 articles.

1. Computational fluid dynamics analysis of different propeller models for a ship maneuvering in calm water;Aram;Ocean. Eng.,2023

2. Evaluation model of low cycle fatigue life of 304 stainless steel based on genetic algorithm optimized BP neural network;Cao;Mater. Res. Express,2022

3. Assessment of ship maneuvering simulation with different propeller models;Deng;J. Hydrodyn.,2022

4. Evaluation and analysis of the static strength of ice-class propellers;Guo;Ocean. Eng.,2021

5. Crack growth models for multiaxial fatigue in a ship's propeller shaft;Hellum;Eng. Fail. Anal.,2021

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1. Influence of Ni content on electrochemical corrosion and tribological behavior of Cu-10Sn coatings by laser cladding;Materials Today Communications;2024-12

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