Earticle

초록

영어

Wireless sensor networks (WSN) are good at security monitoring in coal mine. It is able to rapidly detect diverse parameters, which can reduce human and material losses. And it is an important application that has commercial potential. Coal mine pivotal parameters include Dust Density (Dust), Temperature (Temp), Wind Speed (WindS), Gas Density (GasD) and Carbonic Oxide Density (COD). The data collected by the sensors are sent to the sink node to be processed with information fusion technology. This work presents a strategy for the classification of coal mine status based on sensed data by WSN and the use of unsupervised neural network-the Self-Organizing Map (SOM). The SOM application classifies the coal mine environment into four clusters. An experiment confirms the effectiveness of the proposed approach.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Classifying Information Fusion
  3.1. In View of Information Level
  3.2. In View of Information Type
  3.3. In View of Range
 4. Self-Organizing Map
  4.1. Self-Organizing Map Architecture
  4.2. Self-Organizing Map (SOM) Algorithm
 5. Experiments
  5.1. Related Parameter
  5.2. Experiment Result and Analyze
 6. Conclusions
 References

키워드

저자

• Chanchan Zhao [ School of Computer and Information Technology, Beijing Jiaotong University, College of Information Engineering, Inner Mongolia University of Technology, Hohhot, 010051, P.R. China ]
• Feng Liu [ School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, P.R. China ]
• Xiaowei Hai [ School of Economics and Management, Beijing Jiaotong University, Management College, Inner Mongolia University of Technology, Hohhot, 010051, P.R. China ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Future Generation Communication and Networking

• 간기

  격월간

• pISSN

  2233-7857

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605