融入粒子群与蚁群算法对XML群体概率搜索智能分析

iming at the characteristic of XML for multiobjective optimization and the shortcoming of XML probabilistic query , improvements are given in this paper adopting probabilistic rule of swarm intelligence algorithm. It adopts PSO(Particle Swarm Optimization) to give information pheromone to distribute rapidly and makes use of the ACO(Ant Colony Optimization) to get solution preciously, and following actions are taken in turn towards targets: disassemble, dynamic swarm choose, cross, swarm self-adaptive vary, encode repeatedly, iterative choose, etc., which leads to following good results : widening data search range, improving search precision and convergence efficience, avoiding premature convergence, and reducing complexity of the algorithm. The simulation results show its validity and reliability.