关键词: 基因表达式编程, 染色体, 基因沉默, 符号回归, 多样性

Abstract: The computational effect of Gene Expression Programming（GEP） is better in the problem of symbolic regression with polynomial function as test function, while its computational effect in the more operator number and the non-polynomial function is poor. In this paper, it proposes a gene expression programming algorithm（SFGEP） based on symbolic field, which is based on gene silencing in transgenic biology engineering. The chromosome structure in the SFGEP algorithm is composed of the expression factor domain and the expression gene domain. The chromosomes are explained by the principle of “depth first”, and the gene silencing mechanism in the chromosome interpretation is implemented by using the operator number of different operators to form the inhibitory factor and the position effect of gene expression. The experimental results show that SFGEP, which is greater expression of linear space in comparison with the traditional polygene chromosome GEP, not only has the ability of mining polynomial functions, but also has better performance in non-polynomial function mining with different mesh operators. SFGEP has higher success rate and faster convergence speed.

Key words: gene expression programming, chromosome, gene silencing, symbol regression, diversity