摘要
针对无线传感器网络中不精确、不确定数据问题,提出了将信息处理和粗糙集技术融为一体的新研究思路,并基于分层簇结构给出了一种层次型智能信息处理方法。无线传感器网络实时森林火灾监测的示例与分析表明,该方法在实际应用中,通过从三个层次进行知识约简等智能数据分析,挖掘实用决策规则,使传感器节点仅自动获取和传送有效的最小数据集信息,实现了智能信息处理、能量消耗和系统性能之间的平衡。
This paper specifically considered the imperfect and uncertain data management problem, and proposed a new research idea which integrates rough set theory into the information processing. Furthermore, presented a hierarchical intelligent information processing approach based on clusters on three levels, i.e. local data processing, attribute reduction and rule generation, incompleteness and inconsistency problem. Meanwhile, in practice, as the illustrative examples are shown, by means of intelligent data analysis such as knowledge reduction, a wireless sensor network paradigm for real-time forest fire detection indicates that the novel approach can make it feasible for the sensor nodes to extract and transmit only the efficient minimum set of data automatically, so as to produce high quality information and support decision makings for forest fires prevention and fighting, as a result attaining the desired tradeoffs among intelligent information processing, energy consumption and the aggregate performance.
出处
《计算机应用研究》
CSCD
北大核心
2007年第10期75-78,81,共5页
Application Research of Computers
基金
国家自然科学基金资助项目(60473014)
高等学校博士学科点专项科研基金资助项目(20030486049)
关键词
粗糙集
无线传感器网络
层次型智能信息处理
不确定数据
电源能量效率
簇
rough set theory
wireless sensor networks （WSN）
hierarchical intelligent information processing
uncertain data
battery energy efficiency
cluster
