This paper focuses on the northwest region, which is related to China’s overall ecological security and ethnic stability. This paper selects the neighboring regions of Dingxi City, Gannan Tibetan Autonomous Prefecture and Linxia Hui Autonomous Prefecture as the starting point, deeply and systematically analyzes the impact of different lifestyles on the environment. Using environmental economics, ecological economics, environmental sociology and other related theories, ecological footprint were used to investigate different lifestyles’ impact to environment. Neural network were also used to carry out multi-perspective environmental impact research from the spatial scale and time scale. The research finds that Dingxi, Gannan and Linxia’s different mode of production has led to different lifestyle, and results in different impact on environment. The governments of the three places should take actions to promote ecological civilization and encourage the establishment of an ecologically-friendly and environmentally-friendly way of life so as to reduce the impact on the ecological environment and realize regional sustainable development.

This paper takes the Beijing's main urban as the research object, utilizing machine learning method to quantitatively simulate the location and layout of tourism and leisure facilities. POI data on the grid scale of 1km and the population data of the "the 6th Census" were used, combined with the existing distribution characteristics of tourism and leisure facilities in the Beijing's main urban. Finally, the model is used to simulate and predict each grid in the Beijing's main urban to see if it is suitable for new tourism and leisure facilities. This article simulates 949 suitable sites from the 1548 grids in the Beijing's main urban, and then further filters out 500 sites that need to be prioritized according to the population density of each main urban area to initially realize tourism at a refined scale. Quantitative site selection of leisure facilities. The research found that: ①Comparing the model simulation results with the existing tourism and leisure facilities, the accurate percentage is 95.1%, indicating the level of reliabity. ②The prediction results show that the newly added tourism and leisure facilities in the Beijing's main urban are mainly located in the densely populated areas of the Beijing's main urban. ③ The research attempts to use machine learning algorithms to plan the site selection of tourism and leisure facilities, which can optimize the overall layout and avoid the influence of subjectivity in planning on site selection. It also has certain reference value for the site selection method of other public facilities.

Industrial upgrading and transfer is one of the three key areas in the coordinated development of Beijing-Tianjin-Hebei Region. Meetings, incentives, conferences and exhibitions (MICE) are important means of promoting industrial upgrading. Urban MICE industry, as an important carrier of event activities, become an important gripper for coordinated development of Beijing-Tianjin-Hebei Region. City exhibition space structure plays an dominant role in regional economic development, and it will greatly promote smooth implementation of the coordinated development strategy of Beijing-Tianjin-Hebei Region. In this paper, 13 prefecture-level cities in Beijing, Tianjin and Hebei were selected as research objects, and the data from 2012 to 2018 were selected to establish a gravity model of the attractiveness of MICE cities. With the help of UCINET software, the network density, centrality, cohesive subgroup and core-edge of nodes researches were obtained to analyze the spatial structure characteristics of the attractiveness of MICE cities in Beijing-Tianjin-Hebei Region. The influencing factors of the spatial characteristics of MICE city attractiveness are analyzed by using geographically weighted regression model. The results show that: (1) Beijing, as the overall core area, act as a prominent role. Beijing strengthens the attraction to the superior resources of the surrounding areas, but the network of MICE cities tends to be unbalanced. (2) Overall space forms a subgroup from a single independent subgroup to a subgroup that is spatially separated from each other and acts as an intermediary channel to connect each other, and the core region decreases from 3 to 2. Langfang was removed from the list, leaving Beijing and Tianjin as the core. (3) The influence of supporting facilities, urban environment and population factors on the MICE city attractiveness of Beijing-Tianjin-Hebei Region is increasing gradually. The influence of tourism development level on the MICE city attractiveness of Beijing-Tianjin-Hebei Region is decreasing gradually. The influence of economic development level and Internet development level on the MICE city attractiveness of Beijing-Tianjin-Hebei Region remains unchanged.