Automatic definition of modular neural networks
Adaptive Behavior
Boosting a weak learning algorithm by majority
Information and Computation
The design and analysis of a computational model of cooperative coevolution
The design and analysis of a computational model of cooperative coevolution
Symbiotic evolution of neural networks in sequential decision tasks
Symbiotic evolution of neural networks in sequential decision tasks
Artificial intelligence and soft computing: behavioral and cognitive modeling of the human brain
Artificial intelligence and soft computing: behavioral and cognitive modeling of the human brain
Evolutionary Learning of Modular Neural Networks withGenetic Programming
Applied Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ensemble Methods in Machine Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems (Studies in Fuzziness and Soft Computing)
Soft Computing - A Fusion of Foundations, Methodologies and Applications
New methods for competitive coevolution
Evolutionary Computation
Forming neural networks through efficient and adaptive coevolution
Evolutionary Computation
Construction of classifier ensembles by means of artificial immune systems
Journal of Heuristics
Supervised projection approach for boosting classifiers
Pattern Recognition
Intelligent System for the Diagnosis of Epilepsy
CSIE '09 Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering - Volume 05
Competitive coevolution through evolutionary complexification
Journal of Artificial Intelligence Research
Clinical Decision Support System for Fetal Delivery Using Artificial Neural Network
NISS '09 Proceedings of the 2009 International Conference on New Trends in Information and Service Science
Decision Support System for Fetal Delivery Using Soft Computing Techniques
ICCIT '09 Proceedings of the 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology
Clustering-based hierarchical genetic algorithm for complex fitness landscapes
International Journal of Intelligent Systems Technologies and Applications
Intelligent Medical Technologies and Biomedical Engineering: Tools and Applications
Intelligent Medical Technologies and Biomedical Engineering: Tools and Applications
Evolutionary Design of Neural Network Architectures Using a Descriptive Encoding Language
IEEE Transactions on Evolutionary Computation
A new evolutionary system for evolving artificial neural networks
IEEE Transactions on Neural Networks
Divide-and-conquer learning and modular perceptron networks
IEEE Transactions on Neural Networks
COVNET: a cooperative coevolutionary model for evolving artificial neural networks
IEEE Transactions on Neural Networks
Pareto evolutionary neural networks
IEEE Transactions on Neural Networks
Towards Hybrid and Adaptive Computing: A Perspective
Towards Hybrid and Adaptive Computing: A Perspective
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The complexity of problems has led to a shift toward the use of modular neural networks in place of traditional neural networks. The number of inputs to neural networks must be kept within manageable limits to escape from the curse of dimensionality. Attribute division is a novel concept to reduce the problem dimensionality without losing information. In this paper, the authors use Genetic Algorithms to determine the optimal distribution of the parameters to the various modules of the modular neural network. The attribute set is divided into the various modules. Each module computes the output using its own list of attributes. The individual results are then integrated by an integrator. This framework is used for the diagnosis of breast cancer. Experimental results show that optimal distribution strategy exceeds the well-known methods for the diagnosis of the disease.