# Risk Assessment of Compound Dynamic Disaster Based on AHP-EWM
## 1 Introduction  
The compound dynamic disaster of rock burst and coal and gas outburst (hereinafter referred to as the compound dynamic disaster) refers to a dynamic disaster that appears in the deep mining of coal mines and has some characteristics of rock burst and coal and gas outburst [1; 2; 3; 4]. After the coal mine enters deep mining, the overburden gravity stress and structural stress gradually increase, the stress of the surrounding rock of the stope increases significantly, the gas pressure increases and the coal permeability decreases. The main control factors of the rock burst and coal and gas outburst disasters interact and induce each other, and the disaster process promotes itself, forming a compound dynamic disaster with the characteristics of both rock burst and coal and gas outburst [5; 6; 7]. A risk assessment of compound dynamic disasters forms the basis for the prediction and prevention of compound dynamic disasters and is an integral part of the system for preventing and controlling such disasters. Compound dynamic disaster risk assessment is a technical work that comprehensively analyzes geological factors such as coal and rock mass stress, mechanical characteristics of coal and rock mass, geological structure of working face, coal seam characteristics, coal seam gas content and mining technology factors. By dividing the potential hazardous environment into different risk levels, it provides an objective assessment of the potential hazard environment. The detailed rules for prevention and control of rock burst in coal mines stipulates that \"the comprehensive index method or other effective methods proven by practice can be used for impact risk assessment\". According to the comprehensive indexmethod, a large number of statistical data on rock burst disasters are used to: examine the influence of various geological factors and mining technical factors on rock burst; determine the influence weight of various factors, obtain the comprehensive index of rock burst risk; and divide the rock burst risk level of the mining area. Practice has proven the simplicity and effectiveness of this method [8]. Scholars have optimized the comprehensive index method and introduced the attribute recognition analysis method based on entropy weight [9], the least-squares method and the time-varying weight method [10]; and have integrated the rock burst early warning model based on the fuzzy comprehensive evaluation method [11], the fuzzy comprehensive evaluation method [13] and the back propagation neural network [14]. The above methods have improved the scientific rationality and reliability of the evaluation results of the comprehensive evaluation method to a certain extent. Some scholars use other methods to predict the risk of rock burst, including probabilistic estimates of short-term rock burst risk using ensemble classifiers [15] and the evaluation of the rock burst potential in longwall coal mining using passive seismic velocity tomography and image subtraction technique [16]. Identifying and evaluating coal seam outburst risks is the first step toward preventing and controlling coal and gas outburst disasters. The detailed rules for prevention and control of coal and gas outburst stipulate that \"the coal seams assessed as having outburst risk shall be divided into outburst risk areas and non-outburst risk areas\", and the gas geological analysis method is usually used to divide the outburst risk areas [17]. Some scholars have proposed the multifactor pattern recognition method [18], fuzzy evaluation method [19; 20], extension theory [21], Boruta-Apriori [22] and the back propagation neural network optimized by genetic algorithm and simulated annealing algorithm [23] to carry out coal and gas outburst risk evaluation. To date, a large number of studies have been conducted in order to determine the risk of rock burst and coal and gas outbursts, but there are few studies concerning the risk of compound dynamic disasters in coal mines. [PERSON] et al.