César Hervás Martínez-rekin lankidetzan egindako argitalpenak (23)

2010

  1. A logistic radial basis function regression method for discrimination of cover crops in olive orchards

    Expert Systems with Applications, Vol. 37, Núm. 12, pp. 8432-8444

  2. Designing multilayer perceptrons using a guided saw-tooth evolutionary programming algorithm

    Soft Computing, Vol. 14, Núm. 6, pp. 599-613

  3. Development of a multi-classification neural network model to determine the microbial growth/no growth interface

    International Journal of Food Microbiology, Vol. 141, Núm. 3, pp. 203-212

  4. Ensemble determination using the TOPSIS decision support system in multi-objective evolutionary neural network classifiers

    Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10

  5. Evaluating the performance of evolutionary extreme learning machines by a combination of sensitivity and accuracy measures

    Neural Network World, Vol. 20, Núm. 7, pp. 899-912

  6. Evolutionary q-Gaussian radial basis functions for binary-classification

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  7. Evolutionary q-gaussian radial basis functions for improving prediction accuracy of gene classification using feature selection

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  8. Generalized logistic regression models using neural network basis functions applied to the detection of banking crises

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  9. Hybridizing logistic regression with product unit and RBF networks for accurate detection and prediction of banking crises

    Omega, Vol. 38, Núm. 5, pp. 333-344

  10. Methodology for the recognition and diagnosis of student performance by discriminant analysis and artificial neural networks

    1st International Conference on European Transnational Education: [recurso electrónico] (ICEUTE 2010)

  11. On the suitability of Extreme Learning Machine for gene classification using feature selection

    Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10

  12. Sensitivity versus accuracy in multiclass problems using memetic pareto evolutionary neural networks

    IEEE Transactions on Neural Networks, Vol. 21, Núm. 5, pp. 750-770

2009

  1. A sensitivity clustering method for hybrid evolutionary algorithms

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. A sensitivity clustering method for memetic training of radial basis function neural networks

    ISDA 2009 - 9th International Conference on Intelligent Systems Design and Applications

  3. Classification by evolutionary generalized radial basis functions

    ISDA 2009 - 9th International Conference on Intelligent Systems Design and Applications

  4. Combined projection and kernel basis functions for classification in evolutionary neural networks

    Neurocomputing, Vol. 72, Núm. 13-15, pp. 2731-2742

  5. Hybrid multilogistic regression by means of evolutionary radial basis functions: Application to precision agriculture

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  6. Hyperbolic tangent basis function neural networks training by hybrid evolutionary programming for accurate short-term wind speed prediction

    ISDA 2009 - 9th International Conference on Intelligent Systems Design and Applications

  7. Memetic pareto differential evolution for designing artificial neural networks in multiclassification problems using cross-entropy versus sensitivity

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  8. MultiLogistic Regression using Initial and Radial Basis Function covariates

    IJCNN: 2009 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1- 6