工程科学与技术2017，Vol.49Issue(5)：117-126,10.DOI:10.15961/j.jsuese.201601393
基于表现型的基因表达式编程解空间模型研究
Gene Expression Programming Solution Space Model Based on Phenotype
摘要
Abstract
The theory of solution space model has practical significance to improve the performance of Gene Expression Programming (GEP) algorithms.There are few studies on the GEP solution space model,and the theoretical research on GEP phenotype is also scarce.To address this problem,a GEP solution space model based on phenotype was proposed.Firstly,by defining the height of GEP chromosome phenotype,a theorem and the proof of the upper bound of single gene chromosome and polygene chromosome manifestation were given.To ensure the boundedness and calculability of the GEP phenotype solution space model,the general formula of height upper bound of GEP chromosome phenotype with the minimum number of operators 1 or 2 was calculated,by using the ability of GEP algorithm to find out the function.Secondly,on basis of the definition for upper bound theorem of GEP phenotype height,the GEP solution space model based on phenotype was constructed,and the properties and theorems ofGEP phenotype solution space model were summarized.By further defining the concept of the complete solution space of the GEP phenotype,the distribution of the optimal solution in the GEP phenotype solution space and the complete solution space were explored.It was found that the optimal solution of the subspace in the complete solution space largely increased in proportion to the order number of subspace.Based on the knowledge of phenotypic spatial model,the basic idea and control strategy of limiting the GEP population search space were put forward,and the effectiveness of various GEP improvement algorithms in the literature was explained by the theories of space model.关键词
基因表达式编程/表现型/符号回归/空间模型Key words
gene expression programming/phenotype/symbolic regression/space model分类
信息技术与安全科学引用本文复制引用
郭勇,何锫,张国锋,郭顺超,司永洁..基于表现型的基因表达式编程解空间模型研究[J].工程科学与技术,2017,49(5):117-126,10.基金项目
国家自然科学基金资助项目(61170199) （61170199）
贵州省科技厅联合基金项目资助(20157727 （）
2013GZ12215) （）
