Shaobo Li

Learn More
This chapter proposes a robust design approach that exploits the open-ended topological synthesis capability of genetic programming (GP) to evolve robust lowpass and highpass analog filters. Compared with a traditional robust design approach based on genetic algorithms (GAs), the open-ended topology search based on genetic programming and bond graph(More)
Balanced structure and parameter search is critical to evolutionary design with genetic programming (GP). Structure Fitness Sharing (SFS), based on a structure labeling technique, is proposed to maintain the structural diversity of a population and combat premature convergence of structures. SFS achieves balanced structure and parameter search by applying(More)
Balanced structure and parameter search is critical to evolutionary design with Genetic programming (GP). Structure Fitness Sharing based on a structure labeling technique is proposed to maintain the structural diversity and prevent premature convergence of structures. SFS achieves balanced structure and parameter search by applying fitness sharing to each(More)
The distribution of individuals in a population significantly influences convergence to global optimal solutions. However, determining how to maximise decision space information, which benefits convergence, is disregarded. This paper proposes a type of multi-objective evolutionary algorithm based on decision space partition (DSPEA), and designs the sphere(More)
Previous studies have focused on the association of a gene (EPHX1) encoding microsomal epoxide hydrolase with the carcinogenesis of hepatocellular carcinoma (HCC). In the present study, we performed a meta-analysis to systematically summarize the possible association between EPHX1 genetic polymorphisms and the risk for HCC. We conducted a search of(More)