Wireless Sensor Network nodes correlation method in coal mine tunnel based on Bayesian decision

被引：16

作者：

Chen, Wei ^{[1
,2
]}

Jiang, Xiaorong ^{[1
]}

Li, Xin ^{[1
]}

Gao, Jing ^{[1
]}

Xu, Xinzheng ^{[1
]}

Ding, Shifei ^{[1
]}

机构：

[1] China Univ Min & Technol, Coll Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China

[2] China Univ Min & Technol, State Key Lab Coal Resources & Safe Min, Xuzhou 221116, Jiangsu, Peoples R China

来源：

MEASUREMENT | 2013年 / 46卷 / 08期

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

Tunnel; Path selection; Wireless Sensor Network; Bayesian decision; Nodes association; REDUNDANT DATA ELIMINATION; MINING ASSOCIATION RULES; ALGORITHM; ACTUATION; TRACKING; OBJECT;

D O I：

10.1016/j.measurement.2013.04.018

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The path selection of active objects in the coal mine tunnel has a strong spatial-temporal correlativity. By analyzing the path choices and reasonably selecting relevance among the WSNs nodes in the coal mine tunnel, it is good to reducing the network energy consumption and improving the efficiency of the network monitoring. This paper analyzes the structural characteristics of the coal mine tunnel based on the minimum error Bayesian decision method and the minimum risk Bayesian decision method. According to the probability of moving objects (to the miners, for example) on the choice between tunnels and crossways, we propose the prediction method of path choose based on Bayesian decision, associated Nodes in tunnel and branch. Experiment validation shows that the Bayesian decision method can effectively link nodes. (c) 2013 Elsevier Ltd. All rights reserved.

引用

页码：2335 / 2340

页数：6

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