Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

February 26, 2024


Pages


DOI

Article

Analysis and Research on Mine Safety and Management Methods in the Context of Big Data

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Authors

Jie Xu Affiliation:
School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian, Liaoning, 116023, China.


Abstract

The optimization of mine safety and management methods is critical in the context of big data. This study will explore improving mine safety and management efficiency by utilizing CPS. A mine data interaction mechanism is constructed using CPS technology to realize efficient data collection and processing. The study profoundly explores the data interaction of end devices and the value model of computing resources by analyzing the mine CPS perceptual execution layer. The results show that CPS technology can significantly improve the efficiency of mine safety management. For example, the introduced CRV incentive mechanism significantly improves the utilization efficiency of computing resources. In addition, this study also explores the scheduling strategy of computing resources under multi-objective constraints and the implementation of mine scheduling based on the MOCA-PSO algorithm, which effectively optimizes resource allocation and utilization. The conclusion shows that applying big data technology and CPS can effectively improve mine safety and management, which is of great significance in guiding the future development of the mining industry.


Keywords

Big data, Mine safety, Interaction mechanism, CPS, 94A08


Citation

Xu, J. (2024). Analysis and research on mine safety and management methods in the context of big data. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-0524

Published by: Engineering Journals

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