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Chapter and Conference Paper
Self-Controlling Dominance Area of Solutions in Evolutionary Many-Objective Optimization
Controlling dominance area of solutions (CDAS) relaxes the concepts of Pareto dominance with an user-defined parameter S. This method enhances the search performance of dominance-based MOEA in many-objective opti...
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Chapter and Conference Paper
Genetic Diversity and Effective Crossover in Evolutionary Many-objective Optimization
In this work, we analyze genetic diversity of Pareto optimal solutions (POS) and study effective crossover operators in evolutionary many-objective optimization. First we examine the diversity of genes in the ...
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Chapter and Conference Paper
Adaptive Control of the Number of Crossed Genes in Many-Objective Evolutionary Optimization
To realize effective genetic operation in evolutionary many-objective optimization, crossover controlling the number of crossed genes (CCG) has been proposed. CCG controls the number of crossed genes by using ...
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Chapter and Conference Paper
A Study on Large Population MOEA Using Adaptive ε-Box Dominance and Neighborhood Recombination for Many-Objective Optimization
Multi-objective evolutionary algorithms are increasingly being investigated to solve many-objective optimization problems. However, most algorithms recently proposed for many-objective optimization cannot find...
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Chapter and Conference Paper
Feature Selection in Gait Classification Using Geometric PSO Assisted by SVM
Gait recognition is used to identify individuals by the way they walk. Recent research in automated human gait recognition has mainly focused on develo** robust features representations and matching algorith...