Exploration of virtual city construction and optimization based on deep learning

Abstract

With continuous artificial intelligence and computer graphics technology, virtual cities are receiving widespread attention as an essential digital twin technology, . The core issue of this study is how to choose appropriate neural networks and algorithms to build models to construct virtual cities. The research methods include literature search, research and improvement of deep learning algorithms, and exploration of multi-model combinations. The research conclusion shows that choosing appropriate neural networks and algorithms is the key to building high-quality virtual cities, and targeted improvement and optimization of deep learning algorithms can further improve the accuracy and efficiency of virtual city construction. The strategy of multi-model combination also shows its unique advantages. By integrating different neural networks and algorithms, people can fully utilize their advantages and compensate for each other's deficiencies. With the advancement of technology, more innovative methods and technologies will be applied to this, which will help to build a more realistic virtual world and promote the development and application of virtual cities.