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Found 4 papers, 0 papers with code
Influence of Binomial Crossover on Approximation Error of Evolutionary Algorithms
Although differential evolution (DE) algorithms perform well on a large variety of complicated optimization problems, only a few theoretical studies are focused on the working principle of DE algorithms.
Identification of Interaction Clusters Using a Semi-supervised Hierarchical Clustering Method
Motivation: Identifying interaction clusters of large gene regulatory networks (GRNs) is critical for its further investigation, while this task is very challenging, attributed to data noise in experiment data, large scale of GRNs, and inconsistency between gene expression profiles and function modules, etc.
Inferring Gene Regulatory Network Using An Evolutionary Multi-Objective Method
Inference of gene regulatory networks (GRNs) based on experimental data is a challenging task in bioinformatics.
A binary differential evolution algorithm learning from explored solutions
Although real-coded differential evolution (DE) algorithms can perform well on continuous optimization problems (CoOPs), it is still a challenging task to design an efficient binary-coded DE algorithm.
