Abstract
As the core of artificial intelligence, machine learning has strong application advantages in multi-criteria intelligent evaluation and decision-making. The level of sustainable development is of great significance to the safety evaluation of coal mining enterprises. BP neural network is a classical algorithm model in machine learning. In this paper, the BP neural network is applied to the sustainable development level decision-making and safety evaluation of coal mining enterprises. Based on the analysis of the evaluation method for sustainable development of coal enterprises, the evaluation index system of sustainable development of coal enterprises is established, and a multi-layer forward neural network model based on error backpropagation algorithm is constructed. Based on the system theory of man, machine, environment, and management, and taking the four single elements and the whole system in a coal mine as the research object, this paper systematically analyzes and studies the evaluation and continuous improvement of coal mine intrinsic safety. The BP neural network evaluation model is used to analyze and study the intrinsic safety of coal mines, the shortcomings of the intrinsic safety construction of coal mines are found, and then improvement measures are put forward to effectively promote the safe production of coal mines and finally realize the intrinsic safety goal of the coal mine.
Highlights
Coal mining enterprises have the characteristics of many personnel, scattered operations, many equipment and facilities, wide distribution, bad natural conditions, many unsafe factors, complex working environments, and difficult managements. e workplace is constantly changing [7]. e risk factors of natural disasters and production accidents always affect and restrict the safe production of coal mines
Coal mining is bound to be restricted by the remaining reserves in the mining area, and coal enterprises will face resource depletion sooner or later. erefore, the problem of sustainable development of coal enterprises is becoming increasingly prominent. erefore, it is very necessary to Computational Intelligence and Neuroscience construct a coal mine safety evaluation model based on the research on the evaluation of the sustainable development level of coal enterprises
Coal mine safety theory is put forward in this environment. e coal mine underground is a complex and changeable man-machine environmental system. is paper attempts to evaluate the sustainable development level of coal enterprises by establishing a multi-layer forward neural network model based on the error back propagation algorithm (BP algorithm)
Summary
Coal will still be the main energy source for a long time. At present, the rapid growth of the economy puts forward higher requirements for the development of the coal industry [1–6]. erefore, we must strengthen safety production and ensure the sustainable, stable, and healthy development of the coal industry. Is paper attempts to evaluate the sustainable development level of coal enterprises by establishing a multi-layer forward neural network model based on the error back propagation algorithm (BP algorithm). It can avoid complex mathematical derivation and ensure stable results in the case of sample defect and parameter drift, It can effectively avoid the classical sustainable development evaluation methods, such as the analytic hierarchy process [14–16], fuzzy mathematics [17–22], and principal component analysis [23,24] and cannot avoid the role of people’s experience and knowledge and the personal subjective intention of decision-makers, which is of great benefit to solve the overall decision-making planning of coal enterprises. Is paper will use the system theory to take the coal mine man-machine-environment-management system as the research object, establish the coal mine intrinsic safety evaluation system and evaluation model, comprehensively construct the coal mine intrinsic safety system through the specific and in-depth analysis of various factors of manmachine-environment-management, provide the basis for coal mine safety production and management, and improve the safety production level of the coal mine industry
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