منابع مشابه
A Memetic Pareto Evolutionary Approach to Artificial Neural Networks
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). W...
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The main objective of this work is to automatically design neural network models with sigmoid basis units for binary classification tasks. The classifiers that are obtained achieve a double objective: a high classification level in the dataset and a high classification level for each class. We present MPENSGA2, a Memetic Pareto Evolutionary approach based on the NSGA2 multiobjective evolutionar...
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The main objective of this research is to automatically design Artificial Neural Network models with sigmoid basis units for multiclassification tasks in predictive microbiology. The classifiers obtained achieve a double objective: a high classification level in the dataset and high classification levels for each class. The Memetic Pareto Differential Evolution Neural Network chosen to learn th...
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The main objective of this work is to automatically design artificial neural network, ANN, models with sigmoid basis units for multiclassification tasks in predictive microbiology. The classifiers obtained achieve a double objective: high classification level in the dataset and high classification level for each class. For learning, the structure and weights of the ANN we present an Hybrid Pare...
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Complex networks, like the scale-free model, are observed in many biological and social systems and the application of this topology to artificial neural networks (ANN) leads to interesting considerations. In this paper, we present a preliminary study on the modelling capabilities of ANN with complex topologies. We used an evolutionary algorithm (EA) to train them providing thus the paradigm of...
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ژورنال
عنوان ژورنال: IEEE Transactions on Neural Networks
سال: 2005
ISSN: 1045-9227
DOI: 10.1109/tnn.2004.841794