摘要
通过建立灾害立体网络模型并定义相似空间向量来对区域灾害链规律进行挖掘,同时转化其中的向量发现问题为一种多峰路径优化问题从而利用萤火虫群算法进行求解,并添加变步长、组亮度控制等优化策略,以改善基本GSO算法在收敛速度及求解精度上的不足,最后通过与基本GSO算法的性能对比实验证明了该改进方法的优越性。
The laws of regional disaster chain are mined by building three-dimensional disasters network model and defining the similarity space vectors. At the same time, the vector discover problem in it is transformed into a multimodal path optimisation problem so that the glow- worm swarm algorithm can be applied in problem solving, while the optimisation strategies such as variable step-size and group brightness control are added in order to improve the deficiencies of basic GSO algorithm in convergence speed and solution precision. Performance contrastive experiment with basic GSO algorithm verifies the superiority of this improved method.
出处
《计算机应用与软件》
CSCD
北大核心
2012年第11期29-31,86,共4页
Computer Applications and Software
基金
国家自然科学基金项目(60903174)
中央高校基本科研业务费资助项目(HUST:2012QN087
2012QN088)
河南省重点科技攻关项目(122102310004)
郑州市创新型科技人才队伍建设工程项目(10LJRC190)
关键词
立体灾害网络
灾害链
萤火虫算法
路径优化
多峰函数
Three-dimensional disaster network Disaster chain Glowworm swarm algorithm Path optimisation Multimodal function
