Application of Neural Network Algorithm in Computer Geometry Modeling.

Computer geometric graphics modeling refers to the restoration of the target graphics in the computer graphics environment, and the visual presentation of users, which has been applied in the fields of graphics, virtual reality and computer-aided design. However, the traditional modeling system has some problems, such as low precision and low efficiency, so this paper proposes to use the point cloud data to extract the geometric features of the target graph. In this paper, the Particle swarm optimization-Extreme learning machine (PSO-ELM) algorithm is proposed later, and its principle and operation process are analyzed, and then the algorithm is used to improve the performance of the modeling system. In the comparative experiment of modeling accuracy in this paper, the average modeling accuracy of the intelligent modeling system using the proposed method is 96.97%, while that of the basic system is 94.70%. It is not difficult to see that the experimental results fully reflect the improvement of the modeling accuracy of the modeling system brought by the method in this paper, which is helpful to the application of computer geometric graphics modeling system in practical work. [ABSTRACT FROM AUTHOR]