摘要
在学习PERM算法的基础上 ,指出了影响PERM算法效率的关键因素 ,进而提出了一种改进的PERM算法———IPERM (ImprovedPERM ) .计算结果表明 ,IPERM的计算效率优于PERM算法 。
In this article the factors affecting the efficiency of PERM were pointed and an improved version of PERM IPERM was proposed. In all test cases, the numerical results demonstrated that IPERM outperformed PERM and it was far more efficient than all other fully blind general purpose stochastic algorithms, such as Multi Self Overlap Ensemble(MSOE) and Sequential Importance Sampling with Pilot Exploration(SISPER).
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2004年第7期1-3,共3页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家高技术研究发展计划资助项目 (G1 9980 30 6 0 0 )
湖北省咸宁市白云山林场开发基金资助项目
