群体智能混合算法优化XML数据查询策略  

Optimized query strategy of XML data with swarm intelligent mix algorithms

作　　者：翟学敏[1] 刘渊[1] 刘波[2] 毕蓉蓉[1] 

机构地区：[1]江南大学信息工程学院,江苏无锡214122 [2]中南大学信息学院,长沙410083

出　　处：《计算机应用研究》2008年第10期2970-2972,共3页Application Research of Computers

基　　金：国防基础研究基金资助项目(A1420061266);江苏省教育厅青年骨干教师计划资助项目(2006)

摘　　要：采用路径离散化规则,结合XML半结构化的特点及概率知识,融合粒子群算法与蚁群算法,提出一种优化XML数据查询的概率方法,采用粒子群算法快速生成信息素分布,利用蚁群算法精确求解,达到了优势互补,提高了数据查询的范围和收敛的效率。仿真实验表明这种融合方法具有更好的查询效果。This paper adopted path scatter rule to combine＇tX30 with ACO to improve XML probabilistic query which adopted PSO to make pheromone distribution and made use of ASO to get a value accurately, as a result it developed enough advantages of the two algorithms and the data query range was widen and convergence efficiency was increased. Through simulation experiments, it shows this combine method has a preferable query effect.

关 键 词：粒子群算法 蚁群算法 信息素 路径离散 可扩展标记语言概率查询 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]