Intelligent Optimization Algorithm Application In Fabric Dynamic Simulation

The application of computer to realize3d image simulation is an important issue incomputer graphics, computer vision and other areas. Along with the gradually in-depth study ofcomputer graphics, computer vision and other areas, the application of computer to realize3dimage simulation have been widely used in computer game design, industrial engineeringsimulation, virtual reality and other aspects. As its important application, the real-time3d fabricsimulation technology is also being a research hot spot, because of its special status, such asvirtual reality or human-computer interaction, etc. This paper aims at the key problems which forfabric dynamic simulation model in3d fabric simulation to improve. And use intelligentoptimization algorithm to study and research the parameter of fabric simulation model.The establishment of fabric dynamic simulation model has a lot of kinds. In this paper, thefabric simulation research is based on the mass-spring model belong to the physical model. Themain completed the following several aspects:First, this paper expounds the fabric simulation of the domestic and foreign research presentsituation as well as the fabric simulation modeling method. At the same time, the domestic andforeign research present situations of the intelligent optimization algorithm were introduced.Second, in construction of the fabric simulation model, this paper research the simulationmodel of the fabric, and point out the key technical problems in the fabric simulation model, andput forward the new method to solve the technical problems of fabric simulation model, and usethe new fast dynamic correction method. These show better performance of fabric’s real-action.Third, in this paper, genetic algorithm is proposed to learn and optimize parameters offabric simulation model. Using the traditional genetic algorithm and improved genetic algorithmrealize the optimized and learning。And the parameters are used to realize the fabric dynamicsimulation. Using this method can more quickly get the key parameters of fabric simulationmodel, reflect fabric real effect, and has the breakthrough significance on the fabric simulation. Forth, in this paper, simulated annealing algorithm is proposed to learn and optimizeparameters of fabric simulation model. And using the traditional and improved simulatedannealing algorithm realizes the optimized and learning. And this method also can be very wellto realize fabric model parameter learning.According to the result, we made a comparison and analysis between genetic algorithm andsimulated annealing algorithm to show the good application of intelligent optimization algorithmin fabric dynamic simulation.