Detection Model of Water Logged Area in Goaf Based on Multi-source Data Fusion and Group Intelligence Perception Computing

Abstract

By the perception computing, for improving the efficiency of mine mining and improve its security, and multi-source data fusion and swarm intelligence sensing computing technology have the advantages of fast response rate, high sensitivity and strong applicability, this paper combines multi-source data fusion and group intelligence perception computing technology, through pre detection and analysis of the structure of the mine stratum, discusses the function principle and attention process of two Internet technologies in detail, and establishes a detection model of water logged area in the mine goaf by the group intelligence perception computing. Then, this model is applied to the mine mining between different cities. By comparing the application rate and satisfaction of this detection model between different cities, the corresponding measures to improve the application rate of this detection model are proposed. In a word, this paper combines theory with practice, takes the goaf ponding area as the main target, establishes the corresponding model, and successfully applies it. This exploration model is of great significance to improve the development efficiency of the mine and perception computing.

Authors

  • Xiaoxiao Ma School of Architecture and Intelligent Construction, Zhengzhou Vocational University of Information and Technology, Zhengzhou 450046, China
  • Yeqing Dou School of Architecture and Intelligent Construction, Zhengzhou Vocational University of Information and Technology, Zhengzhou 450046, China

DOI:

https://doi.org/10.31449/inf.v48i23.7003

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Published

12/10/2024

How to Cite

Ma, X., & Dou, Y. (2024). Detection Model of Water Logged Area in Goaf Based on Multi-source Data Fusion and Group Intelligence Perception Computing. Informatica, 48(23). https://doi.org/10.31449/inf.v48i23.7003

Issue

Vol. 48 No. 23 (2024): Online-only issue

Section

Online-only

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