Hybrid Model of WT and ANFIS and Its Application on Time Series Prediction of Ship Roll Motion

Based on the multi time and frequency scale and the nonlinear character of ship roll motion, a hybrid model prediction approach combining wavelet transform (WT) and adaptive neuro-fuzzy inference system (ANFIS) is proposed in this paper. By using multi-resolution nalysis (MRA) of WT, multilevel 1-D wavelet decompositions of roll motion are completed to obtain simple and regular period signals. Then the multiple-input/single-output (MISO) ANFIS model is employed as prediction model for the main decomposed signals above. Finally, a prediction result is given through linear combination. The simulation experiments demonstrate the proposed method can effectively reduce the prediction difficulty and obtain better prediction precision. This method can also be used in ship pitch and heave motion prediction