At present, with the rapid development of the computer Internet, digital media art based on digital technology, to create a high aesthetic works of art and information products. Digital media has gradually evolved into the latest technology in the world, covering a wide range of fields, including education. Its reasonable application in teaching design can significantly improve teaching efficiency and quality. Based on the above background, the purpose of this paper is based on the digital media environment art design professional knowledge communication teaching design and practice. Therefore, this study will be based on the connotation and core of digital media environmental art knowledge construction theory, based on the actual teaching situation in China, to construct a universal teaching mode. This study comprehensively uses the methods of literature research, action research and investigation. First of all, the connotation of digital media characteristics, basic principles, process law and other content of in-depth exploration. Secondly, based on the content of theoretical exploration, combined with the actual teaching situation in China, the design principles and design ideas of the teaching mode are determined, and the "IG-GC two-level six stage knowledge construction teaching mode" is constructed. Finally, the teaching model is applied to real teaching cases, and it is found that the new teaching mode can improve students' scores by 20%. The rationality and effectiveness of the teaching mode are preliminarily verified through standardized tests and questionnaire interviews.

The introduction of logistics theory and logistics technology has made the government and enterprises gradually realize that the development of logistics has an important strategic role, which can effectively solve the changing needs of users, optimize resource allocation, improve the investment environment, and enhance the overall strength and overall competitiveness of the regional economy. This paper carries out matrix-vector multiplication operations and weight update operations, designs a perceptron neural network model, and realizes a simulation platform based on MLP neural network. Moreover, on the basis of the standard MLP neural network, this paper proposes to use the deep learning training mechanism to improve the MLP neural network, which provides effective technical support for the improvement of the prediction model. In addition, through the fusion of deep learning and MLP neural network, an MLP neural network with three hidden layers is determined. Finally, this paper builds a model based on the MLP neural network algorithm, selects the RBF kernel function as the kernel function of the model by referring to the relevant literature, and uses PSO to optimize the combination of parameters. It can be seen from the result of the evaluation index that each evaluation index is relatively small. The result shows that the prediction is accurate, and the empirical result shows the feasibility of the model to predict the demand for industrial logistics in Shanxi Province.