DocumentCode :
2229659
Title :
Empirical prediction methods for rudder forces of a novel integrated propeller-rudder system
Author :
Koushan, Kourosh ; Mesbahi, Ehsan
Author_Institution :
Marine Technol. Res. Inst., Trondheim, Norway
Volume :
1
fYear :
1998
fDate :
28 Sep-1 Oct 1998
Firstpage :
532
Abstract :
Features of the energy saving integrated propeller-rudder system are discussed. Both conventional and artificial neural networks empirical methods for prediction of rudder forces are introduced. These are based on experimental data obtained during cavitation tunnel tests with various configurations of the integrated system coupled with known empirical and theoretical models. Experiments with the integrated system are described. Measured data together with results from both conventional and artificial neural networks approaches are presented. A comparative investigation of both methods is undertaken, both with regard to accuracy and development costs
Keywords :
learning (artificial intelligence); neural nets; ships; accuracy; cavitation tunnel tests; development costs; empirical prediction methods; integrated propeller-rudder system; rudder forces; Artificial neural networks; Costs; Intellectual property; Marine technology; Marine vehicles; Power generation economics; Prediction methods; Propellers; Propulsion; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
OCEANS '98 Conference Proceedings
Conference_Location :
Nice
Print_ISBN :
0-7803-5045-6
Type :
conf
DOI :
10.1109/OCEANS.1998.725804
Filename :
725804
Link To Document :
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