Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Applied statistics: analysis of variance and regression (2nd ed.)
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Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Editing for the k-nearest neighbors rule by a genetic algorithm
Pattern Recognition Letters - Special issue on genetic algorithms
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
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Exponentiated gradient versus gradient descent for linear predictors
Information and Computation
Optimal linear combinations of neural networks
Neural Networks
Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
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MultiBoosting: A Technique for Combining Boosting and Wagging
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Genetic Algorithms and Robotics
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Genetic Algorithms in Search, Optimization and Machine Learning
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Numerical Optimization of Computer Models
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Handbook of Evolutionary Computation
Handbook of Evolutionary Computation
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Artificial Intelligence
Graph Coloring with Adaptive Evolutionary Algorithms
Journal of Heuristics
Schemata, Distributions and Graphical Models in Evolutionary Optimization
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Adaptively Resizing Populations: An Algorithm and Analysis
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Serial and Parallel Genetic Algorithms as Function Optimizers
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PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
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PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Fuzzy Recombination for the Breeder Genetic Algorithm
Proceedings of the 6th International Conference on Genetic Algorithms
An analysis of the behavior of a class of genetic adaptive systems.
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Analyzing the statistical features of CIXL2 crossover offspring
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Self-Adaptive Genetic Algorithms with Simulated Binary Crossover
Evolutionary Computation
A Comparison Study of Self-Adaptation in Evolution Strategies and Real-Coded Genetic Algorithms
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An overview of evolutionary algorithms for parameter optimization
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Empirical investigation of multiparent recombination operators in evolution strategies
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Gradual distributed real-coded genetic algorithms
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Evolutionary ensembles with negative correlation learning
IEEE Transactions on Evolutionary Computation
On self-adaptive features in real-parameter evolutionary algorithms
IEEE Transactions on Evolutionary Computation
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IEEE Transactions on Evolutionary Computation
Using evolutionary algorithms as instance selection for data reduction in KDD: an experimental study
IEEE Transactions on Evolutionary Computation
Cooperative coevolution of artificial neural network ensembles for pattern classification
IEEE Transactions on Evolutionary Computation
Immune network based ensembles
Neurocomputing
Nonlinear Boosting Projections for Ensemble Construction
The Journal of Machine Learning Research
Improving crossover operator for real-coded genetic algorithms using virtual parents
Journal of Heuristics
Distribution replacement: how survival of the worst can out perform survival of the fittest
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Supervised projection approach for boosting classifiers
Pattern Recognition
On the efficiency of crossover operators in genetic algorithms with binary representation
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Comparison of a crossover operator in binary-coded genetic algorithms
WSEAS Transactions on Computers
Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions
Information Sciences: an International Journal
Ensemble approaches for regression: A survey
ACM Computing Surveys (CSUR)
Performance of different techniques applied in genetic algorithm towards benchmark functions
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part I
International Journal of Metaheuristics
Evolutionary algorithms and cross entropy
International Journal of Knowledge-based and Intelligent Engineering Systems
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In this paper we propose a crossover operator for evolutionary algorithms with real values that is based on the statistical theory of population distributions. The operator is based on the theoretical distribution of the values of the genes of the best individuals in the population. The proposed operator takes into account the localization and dispersion features of the best individuals of the population with the objective that these features would be inherited by the offspring. Our aim is the optimization of the balance between exploration and exploitation in the search process. In order to test the efficiency and robustness of this crossover, we have used a set of functions to be optimized with regard to different criteria, such as, multimodality, separability, regularity and epistasis. With this set of functions we can extract conclusions in function of the problem at hand. We analyze the results using ANOVA and multiple comparison statistical tests. As an example of how our crossover can be used to solve artificial intelligence problems, we have applied the proposed model to the problem of obtaining the weight of each network in a ensemble of neural networks. The results obtained are above the performance of standard methods.