计算机工程2012，Vol.38Issue(11)：180-182,185,4.DOI:10.3969/j.issn.1000-3428.2012.11.055
基于CS算法的Markov模型及收敛性分析
Markov Model and Convergence Analysis Based on Cuckoo Search Algorithm
摘要
Abstract
In order to perfect the convergence theory of Cuckoo Search(CS) algorithm, the Markov chain model of the CS algorithm is established and the property of the limited and homogeneous of Markov chain is analyzed. On the basis of this, through the analysis of the state transition process of a group of nest position, the stochastic sequence enters to the optimal state set. And CS algorithm meets the global convergence qualification of random search algorithms. Simulation experimental results show that CS algorithm achieves the global optimization, and the global convergence is ensured.关键词
启发式算法/布谷鸟搜索/Markov链/状态转移/全局收敛性Key words
heuristic algorithm/ Cuckoo Search(CS)/ Markov chain/ state transition/ global convergence分类
信息技术与安全科学引用本文复制引用
王凡,贺兴时,王燕,杨松铭..基于CS算法的Markov模型及收敛性分析[J].计算机工程,2012,38(11):180-182,185,4.基金项目
陕西省教育厅自然科学基金资助项目(2010JK563) （2010JK563）
西安工程大学研究生创新基金资助项目(chx110922) （chx110922）
