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Fault Diagnosis for Ballast Water System Operation on Ships based on SVM

This paper establishes a fault diagnosis model for ballast water system on ships based on support vector machine. We explored how to obtain the parameters of the optimal kernel function by MATLAB. Meanwhile, we compared the accuracy of fault classification with BP neural network and RBF neural network. Numerical experiments for fault classification demonstrate that the proposed method has higher classification accuracy and generalization ability than other two baseline methods.