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Memetic pareto differential evolutionary artificial neural networks to determine growth multi-classes in predictive microbiology

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Abstract

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 the structure and weights of the Neural Networks is a Differential Evolutionary approach based on the Pareto Differential Evolution multiobjective evolutionary algorithm. The Pareto Differential Evolution algorithm is augmented with a local search using the improved Resilient Backpropagation with backtracking–iRprop + algorithm. To analyze the robustness of this methodology, it has been applied to two complex classification problems in predictive microbiology (Staphylococcus aureus and Shigella flexneri). The results obtained show that the generalization ability and the classification rate in each class can be more efficiently improved within this multiobjective algorithm.

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Acknowledgments

This work has been partially subsidized by the TIN 2008-06681-C06-03 project of the Spanish Ministerial Commission of Science and Technology (MICYT), FEDER funds and the P08-TIC-3745 project of the “Junta de Andalucía” (Spain). Manuel Cruz-Ramírez and Francisco Fernndez-Navarro’s research have been funded by the “Junta de Andalucía” Predoctoral Program, grant reference P08-TIC-3745. Javier Sánchez-Monedero’s research has been funded by the “Junta de Andalucía” Ph. D. Student Program.

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Authors and Affiliations

  1. Department of Computer Science and Numerical Analysis, University of Córdoba, Rabanales Campus, Albert Einstein building 3 floor, 14071, Córdoba, Spain

    M. Cruz-Ramírez, J. Sánchez-Monedero, F. Fernández-Navarro, J. C. Fernández & C. Hervás-Martínez

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  1. M. Cruz-Ramírez
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  2. J. Sánchez-Monedero
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  3. F. Fernández-Navarro
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  4. J. C. Fernández
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  5. C. Hervás-Martínez
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Correspondence to M. Cruz-Ramírez.

Additional information

This paper is a very significant extension of a contribution appearing in the 23rd International Conference on Industrial and Engineering & Other Applications of Applied Intelligent Systems (IEA-AIE2010).

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Cruz-Ramírez, M., Sánchez-Monedero, J., Fernández-Navarro, F. et al. Memetic pareto differential evolutionary artificial neural networks to determine growth multi-classes in predictive microbiology. Evol. Intel. 3, 187–199 (2010). https://doi.org/10.1007/s12065-010-0045-9

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