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Coarse-grain parallel genetic algorithms: categorization and new approach
This paper describes a number of different coarse-grain GA's, including various migration strategies and connectivity schemes to address the premature convergence problem. Expand
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Dimensionality reduction using genetic algorithms
We present an integrated feature extraction and classification approach to feature extraction in which feature selection and extraction and classifier training are performed simultaneously using a genetic algorithm. Expand
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Swarmed feature selection
Feature selection is an important part of pattern recognition, helping to overcome the curse of dimensionality problem. Expand
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A Standard GA Approach to Native Protein Conformation Prediction
We report here on further work to determine tertiary structures via genetic algorithms. Expand
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Further Research on Feature Selection and Classification Using Genetic Algorithms
This paper summarizes work on an approach that combines feature selection and data classiication using Genetic Algorithms. Expand
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The Hierarchical Fair Competition (HFC) Framework for Sustainable Evolutionary Algorithms
In this paper, the Hierarchical Fair Competition (HFC) model, including several variants, is proposed as a generic framework for sustainable evolutionary search by transforming the convergent nature of the current EA framework into a non-convergent search process. Expand
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The hierarchical fair competition (HFC) model for parallel evolutionary algorithms
  • J. Hu, E. Goodman
  • Computer Science
  • Proceedings of the Congress on Evolutionary…
  • 12 May 2002
The HFC model for evolutionary computation is inspired by the stratified competition often seen in society and biology. Expand
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Feature Extraction Using Genetic Algorithms
This paper summarizes our research on feature selection and extraction from high-dimensionality data sets using genetic algorithms. We have developed a GA-based approach utilizing a feedback linkageExpand
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Predicting conserved water-mediated and polar ligand interactions in proteins using a K-nearest-neighbors genetic algorithm.
Water-mediated ligand interactions are essential to biological processes, from product displacement in thymidylate synthase to DNA recognition by Trp repressor, yet the structural chemistryExpand
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NSGA-Net: neural architecture search using multi-objective genetic algorithm
This paper introduces NSGA-Net, a multi-objective genetic algorithm for neural architecture search (NAS). Expand
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