Propeller optimization by interactive genetic algorithms and machine learning-Reference-Cited by-同舟云学术

Propeller optimization by interactive genetic algorithms and machine learning

Published:2021-09-05 Issue: Volume: Page:1-16
ISSN:0937-7255
Container-title:Ship Technology Research
language:en
Short-container-title:Ship Technology Research

Author:

Gypa Ioli¹,Jansson Marcus²,Wolff Krister¹,Bensow Rickard¹

Affiliation:

1. Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Gothenburg, Sweden

2. Kongsberg Maritime Sweden AB, Kristinehamn, Sweden

Funder

Chalmers University of Technology Foundation

Swedish Transportation Agency via Lighthouse through the SailProp project

Kongsberg Maritime Sweden AB

University Technology Centre in Computational Hydrodynamics hosted at the Department of Mechanics and Maritime Sciences at Chalmers

Publisher

Informa UK Limited

Subject

Ocean Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/09377255.2021.1973264

Reference31 articles.

1. A Two-Stage Optimisation Method for Full-Scale Marine Propellers Working Behind a Ship

2. Biles J, Anderson P, Loggi L. 1996. Neural network fitness functions for a musical IGA. Proceedings of the International ICSC Symposium on Intelligent Industrial Automation (IIA'96) and Soft Computing (SOCO'96); Reading, UK.

3. A fast and elitist multiobjective genetic algorithm: NSGA-II

4. Gypa I, Bensow R, Wolff K, Gustafsson R. 2020. Interactive evolutionary computation for propeller design optimization of wind-assisted vessels. AIAA AVIATION 2020 FORUM, Virtual Event.

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