Taking the application of BIM technology in the construction project of underground parking garage and supporting commercial buildings in Lvxin Park as an example, this paper analyzes the application of BIM technology in and its effect on the project design modeling, construction project management and construction organization design. Considering the building characteristics of Lvxin Park, the application of BIM Technology is conducted in areas of informatized parametric design, collision inspection, pipeline integration adjustment, layout management and cost management, to makes the project process visible. Then the problems of drawing design and general layout can be found and solved in advance to improve the construction scheme. Lastly, with BIM platform as the core, the useful information in the construction process is loaded into various professional models, and the 3D visual and computable analysis characteristics of BIM model are used to provide data support for project management, so that managers can make more effective decision-making and more refined management.

The light environment created by natural light is preferred by public due to its own economic, natural, pleasant and irreplaceable characteristics. Natural lighting is not only conducive to energy conservation of lighting, but also conducive to increasing the exchange of natural information indoor and outdoor, improving the space health environment and regulating the mood of space users. Making full use of the natural light in the building is of great significance for creating a good light environment, saving energy, protecting the environment and building green buildings. Therefore, it is necessary to optimize the lighting design of buildings. This paper puts forward an idea of natural lighting analysis in building based on the BIM technology and the BP neural network. Taking the CDUT library (library of Chengdu University of Technology) as an example, a 3D visualization model is established by using Revit software to generate the building information file in gbXML format. Then, the gbXML file is imported into Ecotect software to simulate and analyze the indoor light environment of the library, to calculate the natural lighting coefficient, and to quantitatively analyze the impact of window height, glass transmittance and wall material light reflectivity on the indoor light environment. At last, with the help of Weka software, the neural network model based on BP algorithm is established, obtaining the BP neural network model which can predict the variation range of variables under the optimal lighting coefficient.