Virtual Environmental Art Scene Optimization System Based on Genetic Algorithm

As an emerging cultural and artistic form, the virtual environmental art scene system has attracted more and more attention and love from people. This study was based on genetic algorithm to optimize the virtual environmental art scene system and compared the effects of different optimization methods and parameter settings on scene quality through experiments. The experimental results showed that genetic algorithm can significantly improve the realism and artistic quality of the scene, which is better than other optimization methods. The optimal scene design scheme of genetic algorithm had a realism and artistic quality score of 9.5 and 8.6, respectively. The appropriate parameter settings of genetic algorithms also have a significant impact on the optimization effect, with population size, crossover probability, and mutation probability being key parameters that affect the scene optimization effect. The conclusions of this study provide useful guidance for the design and optimization of virtual environmental art scenes, and also provide a foundation for further optimizing the performance of genetic algorithms in actual scene optimization.