Paper
27 September 2024 Research on coal mine gas overrun risk assessment based on analytic hierarchy process-principal component analysis and cloud model algorithm
Bin Hu, Hui Li, Huilin Zhang
Author Affiliations +
Proceedings Volume 13281, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2024); 1328104 (2024) https://doi.org/10.1117/12.3051012
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning, 2024, Zhengzhou, China
Abstract
In response to the inadequacies of the current methods for assessing the risk of coal mine gas overrun limits, including weak foundational techniques and limited visualization, this study integrates the AHP-PCA and cloud model algorithms to construct a more comprehensive and scientifically grounded model for evaluating the risk of coal mine gas overrun limits. The established coal mine gas overrun risk assessment system uses a combination of AHP and PCA to calculate the weights, which effectively solves the complex relationship and uncertainty between various assessment indicators and reduces the influence of subjective and objective factors on the assessment results. The cloud algorithm is used to conduct comprehensive evaluation, so that the evaluation results can be interpreted more visually. The results show that the method can accurately evaluate the risk factors of gas overrun, and provides a certain scientific reference for the prevention and control of coal mine gas overrun risk.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Bin Hu, Hui Li, and Huilin Zhang "Research on coal mine gas overrun risk assessment based on analytic hierarchy process-principal component analysis and cloud model algorithm", Proc. SPIE 13281, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2024), 1328104 (27 September 2024); https://doi.org/10.1117/12.3051012
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KEYWORDS
Clouds

Mining

Risk assessment

Safety

Analytical research

Principal component analysis

Visual process modeling

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