3D Landscape Rendering and Optimization Algorithm of Digital City Based on Convolutional Neural Network

The urban elements necessary for building a smart city and the existing development potential of the city are unclear, leading to many challenges in the construction of smart cities, and new urban problems have emerged one after another. In order to solve the corresponding problems, this paper discusses the functional characteristics of the three-dimensional landscape in the digital city, analyzes the technical ideas of the construction of the three-dimensional landscape system in the digital city, and discusses some key technologies in the construction of the three-dimensional landscape system. In this paper, when establishing the building electricity consumption forecasting model at the city level, a variety of optimizations are made to overcome the defects of the conventional convolution neural network model: (1) the combination model takes the mean value to overcome randomness; Adding statistical rules to eliminate the influence of individual singular prediction values; Learning in real time to improve the accuracy of long-term prediction increased by 26.32%. From the influencing factors of improving the development potential of smart cities, choosing scientific smart city development mode, improving the capacity of smart city construction and strengthening the safeguard measures of smart city development, this paper puts forward some countermeasures, and provides reference suggestions and decision support for solving the problems of smart city construction and development.