Research on the Genetic Neural Network for the Computation of Ship Resistance

摘要

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.