An Improved Nonlinear Fitting Method and Its Application in Function Approximation Based on Particle Swarm Algorithm

Standard normal distribution is widely used in engineering. But it is not so convenient during application, because the analytic expression of the distribution function does not exist. In this paper, the Particle Swarm Algorithm is applied in the nonlinear fitting process of standard normal distribution, and different modified methods are used to obtain analytical expressions of standard normal distribution function. According to the results, it is approved that the improved fitting method can get a better precision.