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Estimation of Navigation Mark Floating Based on Fractional-Order Gradient Descent with Momentum for RBF Neural Network
2021
Mathematical Problems in Engineering
To address the difficulty of estimating the drift of the navigation marks, a fractional-order gradient with the momentum RBF neural network (FOGDM-RBF) is designed. The convergence is proved, and it is used to estimate the drifting trajectory of the navigation marks with different geographical locations. First, the weight of the neural network is set. The navigation mark's meteorological, hydrological, and initial position data are taken as the input of the neural network. The neural network is
doi:10.1155/2021/6681651
fatcat:zfdi5lebtzbctpzmycqqfysjxi