文献类型：会议论文

英文题名：An improved genetic programming algorithm based on bloat control

作者：Zhang, Wei[1]; Hua, De-Liang[2]; Li, Si-Hai[3]; Ren, Zhen[3]; Yu, Zhi-Ling[4]

第一作者：张伟;张维

机构：[1] Gansu University of Chinese Medicine, School of Economic and Management, Lanzhou, 730000, China; [2] Gansu University of Chinese Medicine, Affiliated Hospital, Lanzhou, China; [3] Gansu University of Chinese Medicine, School of Information Engineering, Lanzhou, China; [4] Gansu University of Traditional Chinese Medicine, School of Public Health, Lanzhou, China

第一机构：甘肃中医药大学

通信机构：[1]Gansu University of Chinese Medicine, School of Economic and Management, Lanzhou, 730000, China|[10735]甘肃中医药大学;

会议论文集：2023 4th International Conference on Big Data and Artificial Intelligence and Software Engineering, ICBASE 2023

会议日期：August 25, 2023 - August 27, 2023

会议地点：Hybrid, Nanjing, China

语种：英文

外文关键词：Genetic algorithms

年份：2023

摘要：Aiming at the disadvantages of long training time and high model complexity caused by individual bloat in genetic programming, an improved genetic programming algorithm based on bloat control is proposed. First, species are divided according to the differences between individuals, and individuals are evaluated by adjusted penalty fitness. Then, during the population evolution stage, individuals are selected by density and adjusted penalty fitness, and the improved search strategy is used to search and optimize the selected individuals. The survival mechanism of individuals retains the excellent evolutionary information in the population. Finally, the 7 benchmark functions are simulated and compared with other relevant bloat control algorithms. The experimental results show that the proposed algorithm compared with the 4 comparative algorithms can effectively control individual bloat on the basis of ensuring the optimization ability. ? 2023 IEEE.