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High-efficiency maintenance and control of the deep coal roadway surrounding rock stability is a reliable guarantee for sustainable development of a coal mine. However, it is difficult to control the stability of a roadway that locates near a roadway with large deformation. With return air roadway 21201 (RAR 21201) in Hulusu coal mine as the research background, in situ investigation, theoretical analysis, numerical simulation, and engineering practice were carried out to study pressure relief effect on the surrounding rock after the severe deformation of the roadway. Besides, the feasibility of excavating a new roadway near this damaged one by means of pressure relief effect is also discussed. Results showed that after the strong mining roadway suffered huge loose deformation, the space inside shrank so violently that surrounding rock released high stress to a large extent, which formed certain pressure relief effect on the rock. Through excavating a new roadway near this deformed one, the new roadway could obtain a relative low stress environment with the help of the pressure relief effect, which is beneficial for maintenance and control of itself. Equal row spacing double-bearing ring support technology is proposed and carried out. Engineering practice indicates that the new excavated roadway escaped from possible separation fracture in the roof anchoring range, and the surrounding rock deformation of the new roadway is well controlled, which verifies the pressure relief effect mentioned. This paper provides a reference for scientific mining under the condition of deep buried and high stress mining in western China.

In this article, we study the mural restoration work based on artificial intelligence-assisted multiscale trace generation. Firstly, we convert the fresco images to colour space to obtain the luminance and chromaticity component images; then we process each component image to enhance the edges of the exfoliated region using high and low hat operations; then we construct a multistructure morphological filter to smooth the noise of the image. Finally, the fused mask image is fused with the original mural to obtain the final calibration result. The fresco is converted to HSV colour space, and chromaticity, saturation, and luminance features are introduced; then the confidence term and data term are used to determine the priority of shedding boundary points; then a new block matching criterion is defined, and the best matching block is obtained to replace the block to be repaired based on the structural similarity between the block to be repaired and the matching block by global search; finally, the restoration result is converted to RGB colour space to obtain the final restoration result. An improved generative adversarial network structure is proposed to address the shortcomings of the existing network structure in mural defect restoration, and the effectiveness of the improved modules of the network is verified. Compared with the existing mural restoration algorithms on the test data experimentally verified, the peak signal-to-noise ratio (PSNR) score is improved by 4% and the structural similarity (SSIM) score is improved by 2%.

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In the field of green environmental design, the design system of environmental art is a complex and multidimensional cross-domain fusion system, which can be regarded as a large task system. The development model that combines artificial intelligence (AI) technology and green environment design can not only integrate and analyze problems quickly and efficiently but also provide designers with new design ideas, gradually extending traditional environment design concepts, producing more diverse artistic creation methods, and shifting from a fixed application model to a more diversified artistic development. Therefore, on the basis of summarizing and analyzing previous research works, this paper expounded the research status and significance of green environment design, elaborated the development background, current status, and future challenges of AI technology, introduced the network topology and platform frame structures of green environment design under the AI background, constructed a technical framework of green environment design under the AI background, analyzed the methods and principles of program design and function development, proposed the application model of green environment design under the AI background, conducted design function model optimization and intelligent design process analysis, and finally discussed the evaluation indicators and hierarchical analysis of the green environment design under the AI background. The results show that the application mode of combining AI technology and green environment design can not only help designers break through traditional time and space barriers and use multidimensional thinking but also help designers have a new understanding of artistic design concept and give full play to the advantages of artificial intelligence in a green environment. The study results of this paper provide a reference for further research on the application mode of green environment design under the AI background.