Exogenous parameter selection in a real-valued genetic algorithm

Charles E Kaiser,Gary B Lamont,Laurence D Merkle, George H Gates,Ruth Pachter

Indianapolis, IN（1997）

引用 0|浏览5

暂无评分

摘要

To evaluate the performance of a real valued genetic algorithm (GA) exploiting domain knowledge, we systematically evaluate the effect of exogenous parameters using analysis of variance. The GA platform used for this study is Genocop-III, a real valued, co evolutionary algorithm implementation for numerical optimization. We use the protein structure prediction (PSP) problem as our test domain. Nearly all PSP research assumes the native conformation of a protein corresponds to its global minimum free energy state. Thus, our application integrates Genocop-III with our implementation of the CHARMM energy model as the objective function. Results and conclusions drawn from an extensive experiment set using the polypeptide [Met]-Enkephalin are presented from an exogenous parameter selection perspective

查看译文

关键词

biology computing,genetic algorithms,knowledge based systems,molecular configurations,proteins,charmm energy model,genocop-iii,psp research,analysis of variance,co evolutionary algorithm implementation,domain knowledge,exogenous parameter selection,global minimum free energy state,native conformation,numerical optimization,polypeptide,protein structure prediction,real valued genetic algorithm,amino acids,stochastic processes,energy states,genetic algorithm,weather forecasting,testing,evolutionary algorithm,objective function,evolutionary computation,packaging,protein engineering

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要