An Integrated Entropy Weight and Grey Clustering Method–Based Evaluation to Improve Safety in Mines

Jiskani, Izhar Mithal; Han, Shuai; Rehman, Atta Ur; Shahani, Niaz Muhammad; Tariq, Muhammad; Brohi, Manzoor Ali

doi:10.1007/s42461-021-00444-5

Cited by 24 publications

(12 citation statements)

References 69 publications

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“…The integrated clustering coefficient

for each monitoring point with respect to the grey classes k can be calculated with the following equation [ 76 ]:

…”

Section: Ce Approachesmentioning

confidence: 99%

Performance Evaluation Metrics and Approaches for Target Tracking: A Survey

Yan

et al. 2022

Sensors

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Performance evaluation (PE) plays a key role in the design and validation of any target-tracking algorithms. In fact, it is often closely related to the definition and derivation of the optimality/suboptimality of an algorithm such as that all minimum mean-squared error estimators are based on the minimization of the mean-squared error of the estimation. In this paper, we review both classic and emerging novel PE metrics and approaches in the context of estimation and target tracking. First, we briefly review the evaluation metrics commonly used for target tracking, which are classified into three groups corresponding to the most important three factors of the tracking algorithm, namely correctness, timeliness, and accuracy. Then, comprehensive evaluation (CE) approaches such as cloud barycenter evaluation, fuzzy CE, and grey clustering are reviewed. Finally, we demonstrate the use of these PE metrics and CE approaches in representative target tracking scenarios.

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“…The integrated clustering coefficient

for each monitoring point with respect to the grey classes k can be calculated with the following equation [ 76 ]:

…”

Section: Ce Approachesmentioning

confidence: 99%

Performance Evaluation Metrics and Approaches for Target Tracking: A Survey

Yan

et al. 2022

Sensors

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show abstract

“…All these methods have their own advantages and disadvantages. In order to maximize the advantages of the methods and reduce the influence of method disadvantages, Tian 23 and Chen 24 combined rough set theory with multilevel fuzzy judgment method and Matter-Element analysis, respectively, and JISKANI 12 used entropy weight method and gray clustering method, Qiao Wanguan 25 used DEA- BBC model and DEA-Malmquist index as weight calculation methods to determine the weight size of the indicators and then analyze and evaluate the research object.…”

Section: Introductionmentioning

confidence: 99%

Multi-dimensional safety risk assessment on coal mines under the profitability dilemma

You

Yao

Song

et al. 2023

Sci Rep

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China is a major coal producer, with huge differences in coal production and safety situations between the South and the North. Taking province A as an example, its coal enterprises have low output, poor efficiency, backward equipment, and low-quality personnel. The output accounts for 0.08% of the country, and the number of deaths accounts for 2.2% of the country, the safety situation of coal enterprises in province A is severe. In order to study the safety risk situation of coal mines under difficult conditions, this paper screens 98 factor indexes including multiple subjects such as enterprise managers, front-line workers, government supervisors, external environment, work quality, stress factors, economic factors, and other dimensions. For different data, the indicator weights were calculated using triangular fuzzy number, entropy weight method, CRITIC method, and three rough set methods in a total of six methods. The comprehensive weights of the indicators were obtained using the proposed new comprehensive weight method. The current situation of safety work of four coal mining enterprises and three levels of government supervision departments was evaluated, and the evaluation results were compared with other existing data to verify the reliability of the evaluation system. The horizontal comparison of the evaluation results indicates the main problems of each subject; the longitudinal comparison points out the problems that need to be solved with the assistance of higher-level enterprises and the central government, and corresponding suggestions for coal mining enterprises and government departments are put forward to reduce the safety risks of troubled coal mining enterprises.

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“…In order to integrate the advantages of subjective and objective weights and highlight the goals of the system designer on the basis of reflecting the objective status quo, some experts put forward comprehensive weight calculation methods such as experience coefficient method, and have achieved certain results. In the current field of coal mine safety evaluation in China, DEA and AHP are the mainstream methods for calculating weights (Chang 2019;Qiao 2019;Jiskani, et al, 2021). Using these two methods, the research on coal mine safety management and safety risk assessment has made some progress and achievements, however, there are also some limitations.…”

Section: Introductionmentioning

confidence: 99%

Investigation and application of multi-dimensional safety risk evaluation index system for coal mines in South China

You¹,

Yao

Song

et al. 2022

Preprint

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The occurrence condition of coal seam differs greatly among various regions in China. The uneven development of coal mine safety production level in the North and South China is prominent. Due to the influence of personnel, equipment, mining technology, and other factors, the mortality rate per million tons of coal mines in A province in South China is 27 times the national average level. At present, not only the common factors such as enterprise safety production and government supervision, but also the pressure of regulatory and accountability, the pressure of social stability maintenance, and the external factors such as drastic changes in coal prices, coal supply guarantee, carbon peak and carbon neutralization, have imposed a double impact on coal mining enterprises and government supervision. The situation of coal mine safety production across China is very complex. In order to scientifically figure out the safety risk situation of coal mining enterprises in special periods and special areas, this study takes government supervisors, enterprise managers, underground front-line workers, and external factors as subjects and constructs a multi-dimensional safety risk evaluation system for coal mines in terms of work quality, work pressure, and economic factors. By horizontally and longitudinally comparing the scores of different main index factors, this system can timely discover the problems and weaknesses of supervisors at different levels and managers and front-line workers of different coal mining enterprises in the same region in work quality, work pressure, and economy, which can provide specific targeted suggestions for enterprises and governments on the safety management and safety supervision. This study not only pays attention to the hidden danger screening, risk control, and other factors that can directly reduce enterprise safety risks, but also considers the impact of personnel pressure, economic factors, external environment, and policy changes on the performance of safety production responsibilities by enterprise managers, government supervisors, and enterprise front-line workers. This is an innovation of this study. Finally, based on various subjective and objective weight calculation methods, a new comprehensive weight formula is proposed.

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An Integrated Entropy Weight and Grey Clustering Method–Based Evaluation to Improve Safety in Mines

Cited by 24 publications

References 69 publications

Performance Evaluation Metrics and Approaches for Target Tracking: A Survey

Performance Evaluation Metrics and Approaches for Target Tracking: A Survey

Multi-dimensional safety risk assessment on coal mines under the profitability dilemma

Investigation and application of multi-dimensional safety risk evaluation index system for coal mines in South China

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