DocumentCode
3266586
Title
Research on the Genetic Neural Network for the Computation of Ship Resistance
Author
Ai-Guo, Chen ; Jia-wei, Ye
Author_Institution
Sch. of Civil Eng. & Transp., South China Univ. of Technol., Guangzhou, China
Volume
1
fYear
2009
fDate
6-7 June 2009
Firstpage
366
Lastpage
369
Abstract
The topology structure of the neural network for the computation of ship resistance is designed. The evaluation function adopts msereg. Applying the original experimental data of series 60 ship models, the overall arithmetical crossover and the adaptive mutation, optimize the weights and threshold values of the neural network by genetic algorithm. Then, applying back propagation algorithm to go on training the neural network, develop the optimal genetic neural network for the computation of ship resistance. Easily and quickly calculating ship resistance, the neural network can be applied to research the performance of ship resistance, the optimization of hull form and the optimal matching design of ship engine and propeller.
Keywords
backpropagation; engines; genetic algorithms; neural nets; product design; propellers; ships; adaptive mutation; arithmetical crossover; back propagation; genetic algorithm; msereg; optimal genetic neural network; optimal matching design; ship engine; ship model; ship propeller; ship resistance; threshold value; topology structure; weights value; Computer networks; Design optimization; Engines; Genetic algorithms; Genetic mutations; Marine vehicles; Network topology; Neural networks; Optimal matching; Propulsion; genetic algorithm; neural network; series 60; ship resistance;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3645-3
Type
conf
DOI
10.1109/CINC.2009.34
Filename
5231126
Link To Document