Coal Mining Enterprises Research Articles

Risk evaluation of China’s coal mine production logistics system under coal supply assurance

In order to scientifically and rationally assess the safety condition of coal mine production logistics system, this paper establishes a risk assessment model of coal mine production logistics system based on BWM-Vague set. On the basis of reviewing a large amount of literature and combining the main contributing factors of coal mine production safety accidents in practice, a relatively complete set of safety evaluation index system for coal mine production and logistics system was established, including 4 primary indexes of personnel safety, machine and equipment safety, environmental safety and management safety, and 16 secondary indexes such as the proportion of professional and technical personnel, and the fuzzy comprehensive evaluation method was applied to evaluate the index system. Firstly, the BWM assignment method is used to determine the weights of each index, after which Vague set theory is introduced and experts are invited to evaluate and score each index, and then the two are combined to determine the final comprehensive evaluation. Finally, the model was empirically tested in the context of a coal mine enterprise in Beijing, with a view to improving the safety of the production logistics system in coal mines.

Norwegian and Russian settlements on Svalbard: An analysis of demographic and socio-economic trends

Abstract The Svalbard archipelago is a centre of global research on climate change and also an example of a rapidly changing Arctic area with tourism replacing the traditional mining industry. We compared the different development paths of the Norwegian (Longyearbyen and Ny-Ålesund) and Russian settlements (Barentsburg and Pyramida) on Spitsbergen as part of the Svalbard archipelago using demographic and socio-economic data until 2022 when available, but not focusing on the impacts of COVID-19 and changing geopolitics after 2022. We analysed strategy documents produced by Norway and Russia and by organisations connected to Svalbard. The analysis continued by scrutinising the statistical data available to ascertain if this supported the strategic goals outlined in the documents. Data collection was by direct enquiry to national statistical bureaus, agencies and institutions in Norway and Russia. Secondary data were collected from media publications and social media accounts. Statistics Norway provided very detailed data on demographics and industrial structure, turnover, investments and comprehensive statistics on employees by industry on Norwegian settlements on Svalbard. The results revealed disparities in socio-economic development, striking differences in data availability and in transparency between the Norwegian and Russian settlements. The population in the Norwegian settlements continued to grow during the period 1990–2022 with an increasing number of foreign nationals, and the population in the Russian settlements decreased by 85% at the same time period. The Norwegian settlements exemplify a diversified economy with a growing private sector, and the Russian settlements continued to rely on the town-forming Russian state unitary coal mining enterprise, Trust Arktikugol. While Svalbard presented a prime example of open data and transparency in the environmental sciences, the socio-economic and demographic statistics were lagging behind. Several practical proposals are presented for improved data collection on the Svalbard settlements.

ОБОСНОВАНИЕ ПАРАМЕТРОВ ЭКСКАВАТОРНО-АВТОМОБИЛЬНЫХ КОМПЛЕКСОВ НА УГОЛЬНЫХ РАЗРЕЗАХ С УЧЕТОМ ФАКТОРА НАДЕЖНОСТИ

The article presents the factors affecting the performance of excavators and dump trucks. The main dependences of the technical readiness coefficient of hydraulic excavators (Hitachi, Volvo, Komatsu PC, Liebherr) with a bucket capacity of 1...3.5 m3, in combination with articulated dump trucks Volvo, Bell, BelAZ (with a load capacity of 10-20 tons), quarry dump trucks BelAZ, Terex, Caterpillar, Komatsu (40.100 tons) are given. To increase the efficiency of the process of transporting rock mass at coal mines, the regularities of changes in the performance of quarry dump trucks have been studied. The obtained research results allow us to make a forecast assessment of the annual operational productivity of mining and transport equipment when planning the work of coal mining enterprises in the short term.

Research on risk analysis and prevention policy of coal mine workers' group behavior based on evolutionary game

The analysis and prevention of behavior risk is one of the important measures to reduce accidents. This research adopts the game method to study group safety behavior, and applies the research to behavioral risk prevention in the daily safety management of coal mining enterprises. First, the influencing factors and quantitative relationship of group behavior were determined through investigation. Then, the dynamic game matrix was constructed, and the dynamic game evolution model of "formal group--informal group" was established. The evolution law of group safety behavior was discussed and analyzed from 3 aspects, i.e., management decision, environment, and manager. Finally, the research was applied to coal mine enterprises, and its effectiveness was verified by summarizing and analyzing the behavior violation data for 2 years. It was found that under the influence of management decisions, the level of safe behavior increased by 21.875% in formal groups, and increased by 21.467% in informal groups. In addition, under the influence of the group environment, the level of safe behavior decreased by 79.875% and 86.667% in formal groups and informal groups, respectively. The research explains the dynamic evolution law of coal mine workers and provides a theoretical basis and reference for the management and control of coal mine workers' unsafe behavior.

Методика построения динамической модели управления качеством угля на сложно-структурных месторождениях

Методика построения динамической модели управления качеством угля на сложно-структурных месторождениях

Research on the Prediction Method of Monthly Hidden Danger Quantity in Coal Mine Based on BP Neural Network Periodic Combination Model

To better prevent the occurrence of hidden dangers of coal mine accidents and ensure the safety production of coal mine enterprises. This paper mines and analyses the pattern of historical monthly hidden danger quantity in the coal mine and constructs three models: the traditional backpropagation (BP) neural network model, the BP neural network based on the adaptive moment estimation optimization algorithm (Adam-BP) model, and the BP neural network prediction model with the introduction of monthly moderators (Month-Adam-BP). The experimental results show that the Adam-BP model can improve the prediction accuracy, in which the mean absolute percentage error (MAPE) improves by 8.93%, the root mean square error (RMSE) improves by 8.15%, the postdifference ratio C improves by 0.04, and the small error probability P improves by 0.12; the Month-Adam-BP model with the introduction of the monthly adjustment factor further improves the prediction accuracy, in which MAPE improves by 2.61%, RMSE improves by 5.41%, the postdifference ratio C improves by 0.06, and the small error probability P improves by 0.03. And the Month-Adam-BP model prediction accuracy reaches the level 2 standard with credible prediction effect; it can also be used to predict coal mines with periodic characteristics of hidden hazard data. Our prediction results show that the predicted number of hidden hazards in this coal mine for the next month is 29, which is an increase compared to the number of hidden dangers in the previous month. Thus, the coal mine safety managers need to strengthen the management of hidden hazards further to prevent accidents, which can better serve the standardization of coal mine safety production and ensure the smooth production of the coal mine.

MONITORING THE INFLUENCE OF COAL MAN-MADE LANDSCAPES ON THE ATMOSPHERE OF COAL-MINING REGIONS

According to studies of recent decades, Ukraine is one of the most polluted and environmentally problematic countries in the world. The level of pressure on the environment in Ukraine has increased significantly during the fighting, starting in 2014 in the Donbas, and has deteriorated significantly since 2022. At the present stage of social development, the process of formation and implementation of an effective and efficient state environmental policy, taking into account the existing natural resource potential of the regions and the possibility of their transformation into the national economy, is of particular importance. In recent years, although there has been a decline in production, the annual level of environmental pollution is quite high, including due to incorrect reclamation after the closure of coal mining enterprises. The influence of human activity on the structures of the Earth's surface, today, is especially noticeable in the mining regions, where significant masses of rocks have been brought to the surface and new structures have been created. Human intervention in the process of landscape development leads to new relationships between its components due to the processes of oxidation of rocks brought to the surface and the release of energy and gas mixtures into the atmosphere.
 The coal-mining regions of Ukraine, which are in a state of deep technogenic changes and transformations, have a chance to use the results of intensive geological and technogenic realities for the conclusions of the search for the scientific foundations of nature management and environmental conservation. At the present stage of social development, which is characterized by the acceleration of the pace of scientific and technological progress on the one hand, the aggravation of environmental problems and environmental pollution, on the other hand, the process of formation and implementation of an effective and efficient state environmental policy, taking into account the existing natural resource potential of the regions, is of particular importance.

Uncovering Stakeholders’ Participation to Better Understand Land Use Change Using Multi-Agent Modeling Approach: An Example of the Coal Mining Area of Shanxi, China

Recent decades have witnessed increasing human disruption and the acceleration of fragile natural habitats, especially in coal mining areas in developing countries or regions, which will inevitably lead to sharp land use and cover change (LUCC). Most LUCC models focus more on the research of “land” than “human” in human-land coupled systems, while the simulation and prediction of LUCC involving stakeholders are still deficient. Aiming to reveal the shaping process of LUCC through the stakeholders’ participation, we conducted an in-depth interview in a typical coal mining area of Shanxi, China, and developed an agent-based model by quantifying the stakeholders’ land-use decision-making rules to simulate and predict land use change in different scenarios. The analysis illustrated that the stakeholders’ participation in different periods had shaped the land use pattern in the coal mine area. The area of cultivated land has decreased from 272.34 hm2 to 118.89 hm2, while industrial and mining land increased dramatically by 78.66 hm2 from 2012 to 2019. The attitude and willingness of farmers towards land use varied greatly and were affected by livelihood capital. Part-time farmers whose agricultural income only accounted for 20–80% of the total income were in favor of farmland requisition by coal mining enterprises compared to full-time farmers. We quantified the rules between the attributes of the stakeholders at the micro level and land use changes at the macro level and proposed the multi-agent simulation model, which was effective and verified by a fitting test where the overall accuracy of the Kappa coefficient was 0.83 and could be used to predict future LUCC in research areas by setting the decision parameters in specific scenarios. These outcomes provided a scientific reference for landscape simulation and the prediction of a human-land coupling system while promoting the effectiveness of spatial planning policies.

Targeting the Influences of Under-Lake Coal Mining Based on the Value of Wetland Ecosystem Services: What and How?

Under the growing restrictions of the Chinese eco-environmental policies, the impact of under-lake coal mining on wetlands is receiving increasing attention from both coal mining enterprises and local governments. This paper focuses on the impact of under-lake coal mining on the Nansi Lake wetland from 1991 to 2021. Field measurements, resident surveys, and remote sensing inversion were comprehensively employed to quantitatively assess the impact. The calculation of the assessment indicators refers to the elastic coefficient, the information for which comes from four major categories of ecosystem service values (ESVs) and eight sub-ESVs. According to the results of the remote sensing interpretation and inversion, by 2021 the range had enlarged by 32.3 km2, and the water depth had increased by 1.9 m in the mining-disturbed area relative to 1991. The ESV fluctuations in the Nansi Lake wetland also exhibited a generally increasing trend over time. Our results show that the under-lake mining disturbs the ESVs, but the disturbance is not sufficient to result in significant consequences. Based on the data analysis, we suggest several well-directed, appropriate restoration strategies to achieve the desired objectives and target the response of the ESV changes. Such measures will help to relieve some of the anxiety and concern about the wetland changes caused by the under-lake mining.

Autonomous rectification behavior of coal mine safety hazards under a gambling mind: From an evolutionary game perspective

Safety supervision is an important approach for urging coal mining enterprises to ensure safe production. However, in the face of safety supervision, different interests have a gambling mind for their own benefit, which leads to a loss of risk identification. Moreover, the literature on the analysis of coal mine safety supervision through game methods mainly focuses on how to improve the intensity of supervision. Additionally, research on evolutionary game analysis that considers a gambling mind and research that distinguishes between levels of supervisory intensity are lacking. Therefore, this paper takes the main stakeholders involved in the mine safety supervision, namely, the government supervision departments and the coal mining enterprises as research objects. An evolutionary game model is established. The gambling mind, supervisory intensity, joint liability and other factors are considered in the proposed model. Moreover, this paper also conducts a numerical simulation of the evolutionary game model to analyze the stability of stakeholder interactions and to propose methods for coal mine safety supervision procedures based on the analytical results. The simulation results show that improving the risk identification ability of coal mining enterprises is the key factor for urging coal mining enterprises to take the initiative to rectify safety hazards and avoid accidents. Increasing the frequency of supervision without increasing the penalties can also make the system stable in the optimal state for a long period of time. Increasing joint liability is not conducive to the game system maintaining stability, and has no impact on the supervisory efficiency of government supervision departments. The research results hold great theoretical and practical significance for improving the safety and process management of coal mining enterprises.

The Development of Coal Mine Methane Utilization Infrastructure within the Framework of the Concept “Coal-Energy-Information”

The operation of coal mines is intricately linked with emitting a large quantity of coal mine methane, and in most cases, this methane releases into the atmosphere. In total, according to statistics, coal mining enterprises emit 8% of anthropogenic methane, determining a contribution to greenhouse gas emissions to the amount of 17%. There are various means for coal mine methane utilization. In this study, the concept “Coal-Energy-Information” is proposed. This concept implies both the construction of data processing centers on the industrial sites of coal mines and the usage of coal mine methane. Coal mine methane can be used as a primary energy source for the energy supply of data processing center consumers as well as coal mine consumers with necessary energy resources (electricity, heat, and cooling). Within the framework of the proposed concept, three options of coal mine methane utilization are considered. The first option is the use of gas genset for electrical and thermal energy generation (cogeneration) and their usage for coal mine and constructed data processing centers and consumers’ power supply. The second option is absorption refrigerator usage (with coal mine methane direct burning) for cooling the IT equipment of constructed data processing centers. The last one is the use of a gas genset and absorption refrigerator (trigeneration) for constructed data processing centers’ and coal mine consumers’ energy supplies (electricity, heat, and cooling). In conclusion, it is noted that proposed concept is closely correlated with the program for the development of the coal industry in Russia for the period up to 2035, since it allows creating a base for the implementation of innovative technologies based on digital platforms that ensure the development of coal mining technology without the constant presence of personnel in underground mining facilities.

Occupational incidence in the modern socio-economic conditions of Donbass

An analysis of the current state of occupational pathological assistance to the working contingent of industrial enterprises of the Donetsk People's Republic is presented. When analyzing the dynamics of occupational morbidity for the period 2017-2021, it shows a significant increase from 12.3 cases in 2017 to 30.5 cases in 2021 (per 10,000 workers), mainly due to workers in coal mines. Most of all occupational diseases were registered among workers of the main underground professions - miners of a stope (37.5%) and sinkers (23.3%). The observed increase in occupational morbidity is considered from the standpoint of today's specifics of the working conditions of coal mining enterprises in Donbass. First of all, the absence of a leading occupational hazard with simultaneous multifactorial industrial exposure, often exceeding the threshold values of limit values, as well as a change in operating factors and the intensity of their impact during the length of service. Most cases of occupational diseases identified when workers applied for medical help to the Republican Center for Occupational Pathology had pronounced chronic forms of diseases in workers with work experience in harmful production factors of 20-39 years (up to 75%) and over 50 years of age - more than half of all cases (2020 - 52.7%, 2019 - 51.2%, 2018 - 53%, 2017 - 51.8%). At the same time, when analyzing primary medical documentation (originals of outpatient cards, professional examination cards) working in hazardous conditions, it is noted that more than 80% are «healthy». One of the main reasons for the growth of occupational morbidity is the poor quality of medical examinations carried out by general medical institutions, which causes late detection of occupational and work-related pathologies, the development of advanced forms of general somatic diseases that prevent employees from fulfilling their job duties. In the structure of occupational pathology in the DPR, the largest share falls on diseases caused by physical overload - 44.3%; industrial aerosols - 37.1%; physical factors: vibration - 17.2%, noise - 0.7%. It is concluded that all of the above processes are due to a number of interrelated reasons - a change in the socio-economic situation caused the economic instability of coal enterprises, which led to worsening working conditions, a reduction in the number of employees, an increase in intensive appeals to the Republican Center for Occupational Pathology in order to resolve the issue of the relationship of morbidity with the profession, and , consequently, the solution of social problems through compensation for damage to health.

Research on the Optimization Method of Safety Input Structure in Coal Mine Enterprise

In order to study the application of the Cobb-Douglas production function on the optimization of safety inputs and further reduce accident losses, two safety input structures of a coal mine enterprise were constructed using literature, and the weight order of each safety input indicator was determined by the entropy weight method (EWM) and the analytical hierarchy process (AHP). The Cobb-Douglas production function was used to calculate the accident loss function of the safety input structure, and the accident loss function was obtained by multiple regression analysis. The optimal configuration of safety inputs was obtained by fitting the accident loss function. Finally, the optimal loss and mean squared error (MSE) of the corresponding functions of the two safety input structures were compared. The results show that the optimal configuration of Safety Input Structure 2 is better than that of Safety Input Structure 1, and the MSE of Safety Input Structure 2 is less than that of Safety Input Structure 1. The research results demonstrate that coal enterprises can find more significant indicators by refining the safety input structure and increasing monetary resources for more crucial indicators of safety input to effectively minimize accident loss and boost economic benefits, and to test the quality of safety input structures’ regression function using MSE.

An Overview of Carbon Footprint of Coal Mining to Curtail Greenhouse Gas Emissions

Despite the trend of a transition to “clean” energy, the coal industry still plays a significant role in the global economy. The constant need for raw materials and energy for production leads to an environmental crisis—an increase in the content of greenhouse gases in the atmosphere, especially in the mining regions. The purpose of this study was to analyze the impact of the carbon footprint on the environment and to study ways to reduce the negative impact of coal mining enterprises on the ecology. To analyze the chosen topic, the available reviews and research articles on the impact of the carbon footprint of coal mining enterprises, and the ways to reduce it and restore the biodiversity of wastelands, were used. It was found out that a complete ban on the extraction and use of coal in the industry will not lead to the desired result. The main ways to reduce the negative impact of coal mining enterprises on the environment were considered. The most promising direction for reducing the carbon footprint is the restoration of the vegetation cover by phytoremediation methods and the creation of carbon landfills in reclaimed territories in technogenically polluted coal mining regions.

Анализ применения безвзрывных технологий в условиях криолитозоны

Operation of mining equipment has been analyzed at coal, diamond mining and other min-ing enterprises in conditions of cryolithic zones. Hydraulic breakers, dynamic buckets on ex-cavators, rippers on bulldozers, bar cutters, continuous mining machines, and in some cases, rotary mechanical shovel are used in blast-free mining. It is noted that the hydraulic shovels are characterized with high excavation forces, can be used in selective mining, can clean the foot wall without using a bulldozer, and can reduce or sometimes completely eliminate drill-ing and blasting operations. Boundary values of the face slope angle depending on the ambi-ent temperatures were established during the tests of RS-5500 at the Neryungrinsky open pit mine. Its value is equal to 46º in positive temperature; while during the interseasonal pe-riods the value stands at 60º, and in conditions of extremely low temperatures this value reaches 72º. Experience of using the LIEBHERR hydraulic shovels in building stone quarries shows that the uniaxial compressive strength of the rocks developed without blast pre-conditioning can reach 20-150 MPa. The Caterpillar company proposed a technology for ripping and excavating rocks (up to hard rocks) with quickly replaceable attachment tools. Based on analyzing physical and mechanical properties of the overburden rocks and coal at the deposit with account of cutting forces of the working tool, Mining Institute of the North of Siberian Branch of the Russian Academy of Sciences justified the possibility of using and es-tablished estimated performance parameters of the KCM-2000P Continuous Miner for the rocks and coals of the Elga deposit. Taking into account mining and geological conditions and rock properties of the Elga deposit, specialists of Wirtgen International GmbH calculated the technical and economic parameters of coal and overburden excavation using the Wirtgen 4200SM Surface Miners with loading into the 130-ton dump trucks.

Анализ производственного травматизма и профессиональной заболеваемости на предприятиях угольной отрасли Кузбасса

The level of occupational risks, to which employees of coal enterprises are exposed, is significantly higher than in other branches of industry. Therefore, one of the main tasks of the coal complex development is the prevention of occupational diseases and injury rate based on risk assessment and analysis. The article gives a brief description of the coal industry — in the Kemerovo region. The information is given about the production capacity of enterprises and the volume of coal production in the region. It is established that the high levels of occupational injuries and diseases are explained by the impact on employees of the number of harmful and hazardous factors of the production environment and the labor process. At the same time, 80% of occupational diseases in Kuzbass occur at the coal mining enterprises. Statistical information is presented on the identified cases of occupational diseases at the mines and open pits of the Kemerovo region — Kuzbass in 2021. Possible causes of the high accident rate, including fatal injuries of the personnel, in the mines of Kuzbass over 5 years are identified. It is noted that 91.3 % of all the injuries in the coal industry occur at the enterprises that carry out underground mining. Despite the ongoing accidents and loss of life, the issue of miner safety is not becoming a priority. Many business leaders do not pay enough attention to this issue, and they have little control over the planned steps in this direction. Occupational safety measures are often funded on a residual basis and are not fully implemented. Therefore, improving the working conditions of the coal industry employees, reducing the level of injuries and occupational diseases among them were and remain the urgent tasks.

The Effects of Job Demands and Job Resources on Miners’ Unsafe Behavior—The Mediating and Moderating Role of a Sense of Calling

With the advancement of digital technology, coal mining has gradually become technologically intelligent, but the incidence of coal-mine accidents caused by personal unsafe behavior is still very high. To explore the mechanisms of the significant effects of a sense of calling on miners’ unsafe behavior, based on the job demands–resources (JD–R) model and from the perspective of resource-conservation theory, an empirical test was conducted in two stages with a sample of 660 miners from 6 coal-mining enterprises in China. Job demands and job resources were selected as the independent variables and sense of calling was selected as the mediating and moderating variable. The results showed that job demands had a positive effect on unsafe behavior; a sense of calling weakened the relationship between job demands and unsafe behavior; job resources had a negative effect on unsafe behavior; and a sense of calling partially mediated the relationship between job demands and unsafe behavior. Based on the JD–R model, this study systematically analyzed the occurrence mechanism of unsafe behavior and the effects of a sense of calling on such behavior. It provides practical significance for the management directions of enterprise managers.

Could the Management System of Safety Partnership Change Miners’ Unsafe Behavior?

This paper analyzes the management system of safety partnership in coal mining enterprises through the methods of evolutionary game and optimized behavioral propagation of SEIR, considering the miners’ benefits and losses, as well as the influencing factors from miners and enterprises. It is found that, under the influence of the management system of safety partnership within miners, after the evolutionary game between miner partners, the behavioral strategies and personal benefits of the two miners are both consistent. Moreover, the benefits of individual miner and overall benefits of two miner partners, will affect the miners’ choice of safe behavioral strategies, as a result of which, the coal mines could improve the miners’ benefits through the management system of safety partnership to stimulate the implementation of miners’ safe behavior. Additionally, under the incentive of the management system of the safety partnership, the number of miners implementing unsafe behavior is decreasing, while the number of miners who are not easily affected by unsafe behavior is increasing. When the rewards and punishments of miners are strengthened, the propagation of miners’ safe behavior is accelerated. Finally, the propagation of miners’ safe behavior has a certain spillover effect within a certain range. The results of this paper provide a theoretical basis for the implementation of the management system of safety partnership in coal mining enterprises, which helps enterprises in guiding miners to take up safe behavior, which is better for enterprises’ safe development.

Risk Assessment of Deep Coal and Gas Outbursts Based on IQPSO-SVM.

Coal and gas outbursts seriously threaten the mining safety of deep coal mines. The evaluation of the risk grade of these events can effectively prevent the occurrence of safety accidents in deep coal mines. Characterized as a high-dimensional, nonlinear, and small-sample problem, a risk evaluation method for deep coal and gas outbursts based on an improved quantum particle swarm optimization support vector machine (IQPSO-SVM) was constructed by leveraging the unique advantages of a support vector machine (SVM) in solving small-sample, high-dimension, and nonlinear problems. Improved quantum particle swarm optimization (IQPSO) is used to optimize the penalty and kernel function parameters of SVM, which can solve the optimal local risk and premature convergence problems of particle swarm optimization (PSO) and quantum particle swarm optimization (QPSO) in the training process. The proposed algorithm can also balance the relationship between the global search and local search in the algorithm design to improve the parallelism, stability, robustness, global optimum, and model generalization ability of data fitting. The experimental results prove that, compared with the test results of the standard SVM, particle swarm optimization support vector machine (PSO-SVM), and quantum particle swarm optimization support vector machine (QPSO-SVM) models, IQPSO-SVM significantly improves the risk assessment accuracy of coal and gas outbursts in deep coal mines. Therefore, this study provides a new idea for the prevention of deep coal and gas outburst accidents based on risk prediction and also provides an essential reference for the scientific evaluation of other high-dimensional and nonlinear problems in other fields. This study can also provide a theoretical basis for preventing coal and gas outburst accidents in deep coal mines and help coal mining enterprises improve their safety management ability.

Evolution dynamic of intelligent construction strategy of coal mine enterprises in China

The intelligent construction of coal mining enterprises is the fundamental strategy to prevent and curb major coal mine accidents, and the core technical support to realize the high-quality development of the coal industry. Considering the intelligent construction of coal mining enterprises enabled by emerging information technologies such as 5G and artificial intelligence, this paper constructs a Moran process stochastic evolutionary game model of intelligent construction of coal mining enterprises. Based on the fixed point probability of the Moran process, the probability of successful invasion of the "intelligent construction" strategy and the "traditional production" strategy in the limited coal mining enterprise group is calculated. By comparing the probability of individual fixed point and the probability of neutral mutation, the dominant condition of the strategy under strong selection and weak selection is obtained. The research shows that external stochastic factors, the number and scale of enterprises, the intensity of capacity replacement and the cost-benefit of intelligent construction are the main factors affecting the intelligent construction behavior of coal mining enterprises. When the intelligent construction of coal mining enterprises is in the cultivation period, the intelligent construction of underground coal mines dominated by stochastic factors can be effectively promoted by increasing the intensity of capacity reduction replacement. For the open-pit coal mine dominated by expected payoffs, reducing the number of mining rights and improving the concentration of open-pit coal mining industry will have a better effect on promoting its intelligent cultivation process. When the intelligent construction of coal mining enterprises is in the mature stage, with the improvement of the cost and benefits of intelligent construction, "intelligent construction" strategy will become a general consensus of coal mining enterprises. In addition, this paper analyzes the relevant parameters through specific examples to verify the effectiveness of the conclusions, which provides a scientific basis for effectively accelerating the intelligent construction of coal mining enterprises and promoting the transformation and upgrading of the coal industry.