Curve Fitting Algorithm Based on MLP Neural Network with Spline Weight Function

Aiming at the problem of fast and accurate curve fitting required for aircraft direction trajectory data points, this paper uses the cubic spline function instead of the weights in the MLP neural network, and proposes a method for fitting aircraft trajectory data points using the spline weight function MLP neural network. The paper firstly introduces the MLP neural network as well as the spline weight function. Next, the cubic spline weight function equation is derived. Finally, the method of this paper is compared with the neural network method by performing curve fitting experiments on discrete data points of an airplane trajectory. The results show that the method in this paper reduces the error by 6.9% compared with the neural network method, which is closer to the actual airplane flight trajectory.