Gene Expression Programming With Structured Reusability

YaPing Zheng, Pei He, Chi-Chang Chang and Kangshun Li
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YaPing Zheng: Guangzhou University, China
Pei He: Guangzhou University, China
Chi-Chang Chang: Chung Shan Medical University, Taiwan
Kangshun Li: Dongguan City University, China

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2025, vol. 19, issue 1, 1-27

Abstract: In the field of evolutionary computation, gene expression programming (GEP) has been favored by the public because of its straightforward encoding method. Due to the coding rules for the head and tail on gene, the ability of gene to be constructed as an expression is limited, thereby limiting the expressiveness of individuals. In this article, a variant that uses the standard GEP individual structure and is based on code reuse strategy is proposed to maintain the concise individual representation advantage of GEP and improve the expressive ability of individual. This method can improve the accuracy of the individual and reduce the expression tree complexity. In addition, experiments conducted to predict the recurrence of cervical cancer and malignancy of breast cancer have demonstrated that the predicted performance of GEP and gene expression programming with structured reusability (SR-GEP) has performed better than that of C5.0, but SR-GEP performs best.

Date: 2025
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