Application of whole-implicit algorithm and virtual neural lattice in pelagic longline modeling

This study developed a whole-implicit algorithm and virtual neural lattice to model and simulate the dynamics of pelagic longline gear. The programming, model calculation and behavior simulation of longline dynamics were implemented in R language. Equilibrium state and stable solution of the models were reached. The hooks were more stable in the deepest water layer than that in the midwater layer. It indicated that the whole-implicit method and virtual neural lattice were high efficient and accurate in solving the complicated engineering equations of longline gear, also in the presentation of the motion of longline in sea water.