5 citations · 16 across the 5 of their papers we have counts for
5 papers
Preselection via Classification: A Case Study on Evolutionary Multiobjective Optimization
Jinyuan Zhang, Aimin Zhou, Ke Tang +1
In evolutionary algorithms, a preselection operator aims to select the promising offspring solutions from a candidate offspring set. It is usually based on the estimated or real ob…
An Adaptive Framework to Tune the Coordinate Systems in Evolutionary Algorithms
Zhi-Zhong Liu, Yong Wang, Shengxiang Yang +1
In the evolutionary computation research community, the performance of most evolutionary algorithms (EAs) depends strongly on their implemented coordinate system. However, the comm…
Concept Drift Adaptation by Exploiting Historical Knowledge
Yu Sun, Ke Tang, Zexuan Zhu +1
Incremental learning with concept drift has often been tackled by ensemble methods, where models built in the past can be re-trained to attain new models for the current data. Two…
Convex Hull-Based Multi-objective Genetic Programming for Maximizing ROC Performance
Pu Wang, Michael Emmerich, Rui Li +3
ROC is usually used to analyze the performance of classifiers in data mining. ROC convex hull (ROCCH) is the least convex major-ant (LCM) of the empirical ROC curve, and covers pot…
The Impact of Mutation Rate on the Computation Time of Evolutionary Dynamic Optimization
Tianshi Chen, Yunji Chen, Ke Tang +2
Mutation has traditionally been regarded as an important operator in evolutionary algorithms. In particular, there have been many experimental studies which showed the effectivenes…