Aiming at the problems of relying on initial value and being easy to fall into local optimal solution when using conjugate gradient method to solve Gaussian process hyperparameters,this paper proposes an improved Particle Swarm Optimization (PSO) algorithm based on parametric nonlinear dynamic adjustment strategy and applies it for hyperparameter solving.Firstly,the parameter dynamic adjustment strategy is proposed,and different parameters are adopted for different search stages.Then,according to the concentration adjustment mechanism of immune thought,the global search ability of the algorithm is improved.The simulation results show that:1) The proposed algorithm can quickly converge to the optimal value of the function in the optimal solution;and 2) At the same time,the algorithm is effective for solving the Gaussian process hyperparameters,which can guarantee the accuracy for the establishment of later prediction model.