Research On The Prediction Of Emergency Resources For Major Accidents And Particularly Serious Accidents In Mines Based On Multi-factor Effect

As a pillar industry in China,the mining industry provides an important energy supply and material foundation for the rapid development of the national economy and society.However,due to high labor intensity and risks,major accidents and particularly serious accidents(MAPSAs)have occurred in the mining industry every year,resulting in serious casualties and property losses.The scientific and reasonable forecasting of emergency resource demand and the improvement of emergency rescue capability of the industry are important means to effectively reduce accident losses.Currently,most research on emergency resource prediction in China focus on natural disasters such as earthquakes and floods,but the research of MAPSAs in high-risk industries such as mines is relatively insufficient.In order to realize the prediction of emergency resource demand in the mining industry,this paper starts from the data of 162 MAPSAs from 2014 to 2021,extracts indicators of accident severity according to the key characteristics of accidents,and establishes a prediction model of mine emergency resource demand of MAPSAs based on multi-factor coupling effect by combining the types of emergency resources and the actual demand of emergency rescue.The main research contents,innovation and achievements of this paper are as follows:⑴ Extraction of the key characteristics of mine accidents.By counting162 MAPSAs(46 of which were in the mining industry)that occurred in the past 8 years in China,the accident data were analyzed in terms of overall trends,accident levels,accident types,distribution of high-risk industries,regions of occurrence,and time of occurrence(months,weeks,and periods).It was found that gas explosion is the highest number of accident types in the mining industry,the region with the most accidents was Heilongjiang Province,and the time of the highest occurrence was the fourth quarter.By analyzing the key features of accidents,it provides a scientific basis for government regulatory measures and the implementation of enterprise safety production systems.⑵ Establish a coupled accident severity assessment model.Based on the dissipative structure theory and safety entropy theory,key indicators(industry types,accident types,accident regions,accident time,number of casualties and accident ripple range)were determined on the data of MAPSAs in China in the past 8 years.The entropy weight method was applied to calculating the weight values of indicators and constructing a coupled accident severity assessment model,which can be used to quantitatively calculate the severity of accident damage.⑶ Establish a prediction model for emergency resource demand of mine accidents.Using multiple linear regression analysis theory,combining with the actual rescue process and emergency resources(emergency rescuers,emergency material)needs of 5 common types of mine accidents(gas explosion,poisoning and asphyxiation,fire,roof caving and ribs spalling,water inrush),a prediction model for mine accidents emergency resource demand was established.Six accident cases were selected to validate the model,and the average absolute deviations of the predicted amount of the six emergency resources for each accident were 14.44 %,16.04 %,11.52 %,9.86 %,11.20 %,and 7.27 %,respectively.It achieves more accurate prediction results under the condition of information asymmetry,improves the speed of emergency decision-making,shortens the response time of emergency rescue and emergency resource allocation,and provides a theoretical basis for improving the emergency rescue capability of the mining industry.