Algorithms for clustering data
Algorithms for clustering data
A note on genetic algorithms for large-scale feature selection
Pattern Recognition Letters
Perceptron redux: emergence of structure
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Efficient genetic algorithms for training layered feedforward neural networks
Information Sciences—Informatics and Computer Science: An International Journal
Neurofuzzy adaptive modelling and control
Neurofuzzy adaptive modelling and control
Alternative Neural Network Training Methods
IEEE Expert: Intelligent Systems and Their Applications
Designing Neural Networks using Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Towards the Genetic Synthesisof Neural Networks
Proceedings of the 3rd International Conference on Genetic Algorithms
Further Research on Feature Selection and Classification Using Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
Neuron Reordering For Better Neuro-genetic Hybrids
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
A Genetic Hybrid For Critical Heat Flux Function Approximation
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Nonlinear feature extraction using a neuro genetic hybrid
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Artificial neural networks for feature extraction and multivariate data projection
IEEE Transactions on Neural Networks
A nonlinear projection method based on Kohonen's topology preserving maps
IEEE Transactions on Neural Networks
Stock prediction based on financial correlation
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Nonlinear feature extraction using a neuro genetic hybrid
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A Hybrid Nonlinear-Discriminant Analysis Feature Projection Technique
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Neuro-genetic system for stock index prediction
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Evolutionary neural networks for practical applications
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Feature extraction is a process that extracts salient features from observed variables. It is considered a promising alternative to overcome the problems of weight and structure optimization in artificial neural networks. There were many nonlinear feature extraction methods using neural networks but they still have the same difficulties arisen from the fixed network topology. In this paper, we propose a novel combination of genetic algorithm and feedforward neural networks for nonlinear feature extraction. The genetic algorithm evolves the feature space by utilizing characteristics of hidden neurons. It improved remarkably the performance of neural networks on a number of real world regression and classification problems.