Research and Exploration of Land Use in Core Area of Urban Central Rail Transit Station Based on AI Technology

Abstract

Land use of urban central rail transit station core area is an important part of the TOD model research, which is of great significance to urban agglomeration and sustainable development. Base on the characteristics of “Node-place” in the rail transit station area, this paper constructs a land use database framework in the station core area, and determines the land use index factors according to the cases field investigation and data analysis. By comparing the features of BP artificial neural network and depth neural network, this paper builds two technical routes: “Land use prediction simulation of station core area based on BP artificial neural network” and “land use planning scheme of station impact area based on deep neural network”. This paper explored the interdisciplinary method of using artificial intelligence (AI) technology to study the land use of urban central rail transit station core area and designs the technical route, which is of great significance to promote the efficient use of urban land in rail station area and the sustainable development of cities.