Wireless Sensor Network nodes correlation method in coal mine tunnel based on Bayesian decision
Wireless Sensor Network nodes correlation method in coal mine tunnel based on Bayesian decision
复制标题
基于贝叶斯决策的煤矿巷道无线传感器网络节点关联方法
DOI：
10.1016/j.measurement.2013.04.018
复制
发表时间：
2013-10-01
期刊：
影响因子：
5.6
通讯作者：
Ding, Shifei
中科院分区：
文献类型：
--
作者：
Chen, Wei;Jiang, Xiaorong;Ding, Shifei
煤矿巷道活动对象的路径选择具有较强的时空相关性。通过分析路径选择，合理选择煤矿巷道内无线传感器网络节点之间的相关性，有利于降低网络能耗，提高网络监控效率。基于最小误差贝叶斯决策法和最小风险贝叶斯决策法对煤矿巷道的结构特性进行了分析。根据移动物体（例如矿工）在隧道和十字路口之间选择的概率，提出了基于贝叶斯决策、隧道和分支中关联节点的路径选择预测方法。实验验证表明，贝叶斯决策方法能够有效链接节点。 (c) 2013 Elsevier Ltd. 保留所有权利。
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.