Modeling of the ship steady turning motion based on multiblocks of fuzzy cognitive maps

Research on modeling ship motions is beneficial to promote safety in the shipping industry. However, it has always been a difficult point in the representation of this complex nonlinear system. The fuzzy cognitive map (FCM) can represent nonlinear systems effectively, and its divide-and-conquer strategy simplifies the modeling process. We propose a scheme of multiblocks of FCMs for modeling the steady turning motion of ships. First, the physical variables of the maneuvering mathematical modeling group (MMG) are employed as the conceptual nodes, and the causal links between concepts are analysed to establish the structure of FCMs. Subsequently, combined with normalized data, the loss function is optimized by least squares method, and the automatically partitioned of the training data and the parameters estimation of the FCMs in each data block are completed simultaneously provided that the designated required accuracy are satisfied. Finally, the multiblocks FCMs are integrated into an overall Ship-FCMs system after verification by the testing data. Experiments are conducted based on the simulation data of ?Yulong?, which demonstrate the effectiveness of the proposed algorithm.