Chaotic Clonal Genetic Algorithm for Protein folding model

摘要：

To improve protein folding simulations, a novel chaotic clonal genetic algorithm (ccga) was investigated on a 2d lattice model. The novel algorithm combines chaos operator, clonal selection algorithm, and genetic algorithm. We compared ccga with standard genetic algorithm (sga) and immune genetic algorithm (iga) for various chain lengths. It has shown that ccga not only find global minima more reliably, but also be significantly faster in convergence.

关键词： chaotic clonal genetic algorithm protein folding model

作者: Yudong Zhang Lenan Wu Yuankai Huo Shuihua Wang

作者单位: School of Information Science and Engineering, Southeast University, Nanjing, China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 120-124

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）