Research on parameters estimation of probability integral model based on wolves pack algorithm

The model of probabilistic integral method is a typical multivariate complex nonlinear function, and some parameters are correlated, which makes the parameter inversion of probabilistic integral method a hot and difficult problem in mining subsidence data processing.WPA(wolf pack algorithm), as a new swarm intelligence algorithm, has been successfully applied in multi-dimensional knap-solving problems, optimal operation of hydroelectric power stations and reservoirs, as well as complex nonlinear optimization problems such as travel agents.In view of this, this paper introduces WPA into parameter inversion of probabilistic integration method for the first time, and constructs a model parameter inversion method based on WPA.The research results show that the model parameters of WPA inversion probability integral method have higher accuracy, better accuracy, good robustness, and meet engineering application standards.The results of this paper have important reference value for accurate parameter inversion of probabilistic integral method.