The invention discloses a ship flow prediction method based on VMD-FOA-GRNN. The method comprises the following steps: 1, preprocessing ship flow data; 2, performing mutation inspection on the preprocessed ship flow data, and selecting non-mutated ship flow data; 3, performing VMD on the ship flow data which are not mutated, generating a series of IMFs with different frequency scales, and obtaining the decomposed ship flow data; 4, constructing a GRNN based on the FOA, and predicting the decomposed ship flow data to obtain a predicted value; and 5, based on the taste concentration judgment function, performing error analysis on the predicted value and the true value to obtain an average absolute percentage, and completing prediction of the ship flow data. According to the method, the problems that an existing prediction method is not high in prediction precision and does not have universal applicability are solved, the prediction precision of the ship flow is improved based on the generalized regression neural network of variational mode decomposition and fruit fly optimization, the problem of universal applicability of time sequence prediction of complex nonlinear time is solved,and the stability is improved.