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Simulation of Chinese Coal Mine Safety Supervision System Performance Based on Netlogo Platform

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Coal mine safety supervision efficiency is a complex system output affected by multiple factors. This paper constructs the agent model of a coal mine safety supervision system with multi-agent modeling and investigates a simulation system based on Netlogo. The decision mechanism of coal mine safety supervision performance is analyzed by observing dynamic changes of the supervision activities, system risks, and success rate of processing violations. Values of input variables, such as the scale and characteristics of violation agent, decision support, functional cooperation, and supervisory power are altered to conduct theoretical research on coal mine safety management. Limitations and further improvements in the simulation system are summarized.
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Keywords: BP Neural Network; Modeling and Simulation Based on Multi-Agent; Netlogo; Safety Supervision Efficiency; Security

Document Type: Research Article

Affiliations: School of Management, China University of Mining and Technology, Xu Zhou, Jiang Su, China

Publication date: 01 August 2016

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  • Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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