Abstract:

This paper constructs a 3D animation modeling evaluation model with Particle Swarm Optimization (PSO) algorithm and BP network in view of the issues of easy falling of standard BP neural network into local minimum and the global searching of PSO. We apply the model to the generation of 3D animation modeling. It fully utilizes the characteristic of global searching of PSO and optimizes the weights and thresholds of BP network, which makes mean-square error less than or equal to the preset value. Experimental results show that the approach improves the convergence rate and convergence precision of BP network based on the guarantee of the global optimization result. It has preferable evaluation capability in the evolution of 3D animation modelings and improves the quality of 3D animation modelings.

Key words: particle swarm optimization, BP neural network, global optimization, 3D animation modeling evaluation