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Advances in neural information processing systems 2
Evolutionary computation: toward a new philosophy of machine intelligence
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Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Towards designing artificial neural networks by evolution
Applied Mathematics and Computation - Special issue on articficial life and robotics
Memetic algorithms: a short introduction
New ideas in optimization
Neural Networks: A Comprehensive Foundation
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Applied Intelligence
Training Product Unit Neural Networks with Genetic Algorithms
IEEE Expert: Intelligent Systems and Their Applications
Alternative Neural Network Training Methods
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Multiple Objective Optimization with Vector Evaluated Genetic Algorithms
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Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Making use of population information in evolutionary artificialneural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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ICAL 2003 Proceedings of the eighth international conference on Artificial life
Evolutionary Computation - Special issue on magnetic algorithms
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Neural Processing Letters
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HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
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Computers and Operations Research
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HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
PEEC: evolving efficient connections using Pareto optimality
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Application notes: MEBRA: multiobjective evolutionary-based risk assessment
IEEE Computational Intelligence Magazine
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
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EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Multiobjective evolutionary neural networks for time series forecasting
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
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Computers and Operations Research
Sensitivity versus accuracy in multiclass problems using memetic Pareto evolutionary neural networks
IEEE Transactions on Neural Networks
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Weighting Efficient Accuracy and Minimum Sensitivity for Evolving Multi-Class Classifiers
Neural Processing Letters
Multiobjective optimization of ensembles of multilayer perceptrons for pattern classification
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Multi-objective hybrid evolutionary algorithms for radial basis function neural network design
Knowledge-Based Systems
Solving rotated multi-objective optimization problems using differential evolution
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
A multi-objective neural network based method for cover crop identification from remote sensed data
Expert Systems with Applications: An International Journal
Effective diversity maintenance in deceptive domains
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Information Sciences: an International Journal
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Evolutionary Artificial Neural Networks (EANN) have been a focus of research in the areas of Evolutionary Algorithms (EA) and Artificial Neural Networks (ANN) for the last decade. In this paper, we present an EANN approach based on pareto multi-objective optimization and differential evolution augmented with local search. We call the approach Memetic Pareto Artificial Neural Networks (MPANN). We show empirically that MPANN is capable to overcome the slow training of traditional EANN with equivalent or better generalization.