Empirical Mode Decomposition Based LSSVM for Ship Motion Prediction

摘要

An empirical mode decomposition (EMD) based Lease square support vector machines (LSSVM) is proposed for ship motion prediction. For this purpose, the original ship motion series were first decomposed into several intrinsic mode functions (IMFs), then a LSSVM model was used to model each of the extracted IMFs, so that the tendencies of these IMFs could be accurately predicted. Finally, the prediction results of all IMFs are combined to formulate an output for the original ship motion series. Experiments on chaotic datasets and real ship motion data are used to test the effectiveness of the proposed algorithm.