Sensitivity of mountain landslide based on Markov model and aerobic training management

In this paper, we will use MATLAB to create a Markov model, determine the input and output membership functions of the study area, and import the data of the study area into the model. The ROC method is used to prove the accuracy of the sensitivity distribution map of mountain landslide disaster and the feasibility of the model in the sensitivity assessment of mountain landslide. It also shows the reliability and applicability of the selected factors. Based on GIS technology, the influencing factors of sensitivity coefficient of landslides in mountainous areas can be extracted. According to the spatial distribution characteristics of landslides, six influencing factors of landslides and their spatial distribution relationships are analyzed: height, slope, geological lithology, terrain curvature, terrain humidity index, and runoff intensity index. Training management combined with aerobic exercise is helpful to improve people’s body shape. The effect of “resistance training + aerobic exercise” training method adopted by experimental group 1 on body shape is the most significant. The arm circumference of the male experimental group increased, while that of the female experimental group decreased. In the training management, different combination methods of resistance training and aerobic exercise have no significant effect on the improvement of the muscle strength of the subjects after the experiment. By analyzing and comparing the changes of cardiopulmonary function indexes of the subjects before and after training, this paper expounds the training effect of blood flow restriction under different pressures combined with low-intensity aerobic exercise on cardiopulmonary function. In this paper, through the study of the Markov model and mountain landslide sensitivity, it is applied to aerobic training management, which promotes the better improvement of people’s body shape. © 2021, Saudi Society for Geosciences.