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Publicações
Luo, W., Guedes Soares, C. e Zou, Z. (2016) , “Parameter Identification of Ship Manoeuvring Model based on particle swarm optimization and support vector machines”, 2.1.178 - JOMAE 138 (2016) - 031Journal of Offshore Mechanics and Artic Engineering,Vol 138, pp. 031101-1
Combined with the free-running model tests of KVLCC ship, the system identification based on Support Vector Machines (SVM) is proposed for the prediction of ship manoeuvring motion. The hydrodynamic derivatives in an Abkowitz model are determined by the Lagrangian factors and the support vectors in the SVM regression model. To obtain the optimized structural factors in SVM, Particle Swarm Optimization (PSO) is incorporated into SVM. To diminish the drift of hydrodynamic derivatives after regression, a difference method is adopted to reconstruct the training samples before identification. The validity of the difference method is verified by correlation analysis. Based on the Abkowitz mathematical model, the simulation of ship manoeuvring motion is conducted. Comparison between the predicted results and the test results demonstrates the validity of the proposed methods in this paper.
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