Risk assessment of floor water inrush based on TOPSIS combined weighting model: a case study in a coal mine, China

Li, Qiang; Lu, Cunjin; Zhao, Hui

doi:10.1007/s12145-022-00898-1

Cited by 6 publications

(2 citation statements)

References 43 publications

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“…Table 1 analyzes the related works that have been studied to generate CROWM according to the following characteristics: calculation of weights (objective or not); techniques employed; use of communalities in performance evaluation; advantages and disadvantages; presence or absence of PCA validation tests; consideration of non-beneficial criteria in the PCA; and, finally, whether they can generate performance evaluation of the alternatives. Regarding the generation of criteria weights, the analysis of methods that combine PCA and MCDA can be divided into approaches based on the DM's assessment and those that use objective weights, like KPCA-TOPSIS [48], PCA-TOPSIS [54], PCA-PROMETHEE [57], WIRI [52] and P-SPCA, P-PFA, and P-SRD [50]. This distinction is crucial, as objective methods focus exclusively on the data, free from subjective influences, which is necessary to ensure an unbiased and evidence-based analysis.…”

Section: The Crowm Methodsmentioning

confidence: 99%

Optimization of Obstructive Sleep Apnea Management: Novel Decision Support via Unsupervised Machine Learning

de Araújo Costa,

Terra,

de Souza Rocha Junior

et al. 2024

Informatics

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This study addresses Obstructive Sleep Apnea (OSA), which impacts around 936 million adults globally. The research introduces a novel decision support method named Communalities on Ranking and Objective Weights Method (CROWM), which employs principal component analysis (PCA), unsupervised Machine Learning techniques, and Multicriteria Decision Analysis (MCDA) to calculate performance criteria weights of Continuous Positive Airway Pressure (CPAP—key in managing OSA) and to evaluate these devices. Uniquely, the CROWM incorporates non-beneficial criteria in PCA and employs communalities to accurately represent the performance evaluation of alternatives within each resulting principal factor, allowing for a more accurate and robust analysis of alternatives and variables. This article aims to employ CROWM to evaluate CPAP for effectiveness in combating OSA, considering six performance criteria: resources, warranty, noise, weight, cost, and maintenance. Validated by established tests and sensitivity analysis against traditional methods, CROWM proves its consistency, efficiency, and superiority in decision-making support. This method is poised to influence assertive decision-making significantly, aiding healthcare professionals, researchers, and patients in selecting optimal CPAP solutions, thereby advancing patient care in an interdisciplinary research context.

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Section: The Crowm Methodsmentioning

confidence: 99%

Optimization of Obstructive Sleep Apnea Management: Novel Decision Support via Unsupervised Machine Learning

de Araújo Costa,

Terra,

de Souza Rocha Junior

et al. 2024

Informatics

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“…AT mainly plays a role in blocking the sandstone fissure water above the coal seam [30]. However, due to the disturbance of mining, the roof will continuously collapse and generate induced fractures resulting in a decrease in the water resistance of the waterproof layer.…”

Section: Evaluation Indicatorsmentioning

confidence: 99%

Risk Assessment and Zonation of Roof Water Inrush Based on the Analytic Hierarchy Process, Principle Component Analysis, and Improved Game Theory (AHP–PCA–IGT) Method

2023

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With the large-scale mining of deeply buried coal seams, the risk of roof water inrush increases during mining. In order to ensure safe mining, it is necessary to predict the risk potential of water inrush from the roof aquifer. This study introduces a coupling evaluation method, including the analytic hierarchy process (AHP), principal component analysis (PCA), and improved Game theory (IGT). This paper takes the water inrush from the roof aquifer of the 11-2 coal seam in Kouzidong mine as the research object. An evaluation index system is constructed by selecting six evaluation factors, including the aquitard effective thickness, aquiclude thickness, the ratio of sandstone to mudstone, rock quality designation, fault fractal dimension, and wash water quantity of geological log. The comprehensive weighting method based on IGT is used to optimize the subjective and objective weighting values obtained by AHP and PCA methods in turn, and an AHP–PCA–IGT evaluation model is established to divide and evaluate the water inrush risk zonation of the roof aquifer. The risk degree of the water inrush gradually decreases from the center to the north–south, and the main areas with relatively high risks and higher risks are distributed in a small part of the western and eastern regions. Finally, combining various drilling data examples, drilling pumping tests, and water inrush sites, the accuracy of the predicted results is validated through the vulnerability fitting percentage (VFP). The predictions are basically consistent with the actual results, and this study lays a theoretical foundation for the prevention and control of water inrush hazards.

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Quantitative risk assessment of rainstorm-induced flood disaster in Piedmont plain of Pakistan

Chang,

Zhou,

Dou

et al. 2025

Sci Rep

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Risk assessment of floor water inrush based on TOPSIS combined weighting model: a case study in a coal mine, China

Cited by 6 publications

References 43 publications

Optimization of Obstructive Sleep Apnea Management: Novel Decision Support via Unsupervised Machine Learning

Optimization of Obstructive Sleep Apnea Management: Novel Decision Support via Unsupervised Machine Learning

Risk Assessment and Zonation of Roof Water Inrush Based on the Analytic Hierarchy Process, Principle Component Analysis, and Improved Game Theory (AHP–PCA–IGT) Method

Quantitative risk assessment of rainstorm-induced flood disaster in Piedmont plain of Pakistan

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