2007 |
10 | EE | Bruno M. Nogueira,
Tadeu R. A. Santos,
Luis E. Zárate:
Comparison of Classifiers Efficiency on Missing Values Recovering: Application in a Marketing Database with Massive Missing Data.
CIDM 2007: 66-72 |
9 | EE | Luis E. Zárate,
Sergio M. Dias,
Mark A. J. Song:
FCANN Method Applications for Knowledge Extraction From Previously Trained ANN.
IJCNN 2007: 649-654 |
8 | EE | Luis E. Zárate,
Fabricio R. Bittencout:
Neural Networks Applied to Adjustment and Combination of the Control Actions for the Cold Rolling Process.
IJCNN 2007: 655-660 |
2006 |
7 | EE | Luis E. Zárate,
Elizabeth Marques Duarte Pereira,
Leonardo A. R. Oliveira,
Victor P. Gil,
Tadeu R. A. Santos,
Bruno M. Nogueira:
Techniques for Training Sets Selection in the Representation of a Thermosiphon System Via ANN.
IJCNN 2006: 2736-2741 |
6 | EE | Luis E. Zárate,
Elizabeth Marques Duarte Pereira:
Parametric Analysis of Solar Collectors Through Sensitivity Factors Via Artificial Neural Networks.
IJCNN 2006: 2742-2748 |
5 | | Mark A. J. Song,
Luis E. Zárate,
Sergio M. Dias,
A. Alvarez,
B. Soares,
Bruno M. Nogueira,
Renato Vimieiro,
Tadeu R. A. Santos,
N. Vieira:
SOPHIANN: A Tool for Extraction Knowledge Rules from ANN Previously Trained A Case Study.
SEKE 2006: 631-638 |
2004 |
4 | | Luis E. Zárate,
Paulo Alvarenga,
Romero Paoliello,
Thiago Ribeiro:
Data Mining Application to Obtain Profiles of Patients with Nephrolithiasis.
ICEIS (2) 2004: 104-109 |
3 | | Luis E. Zárate,
Elizabeth Marques Duarte Pereira,
Daniel A. Soares,
João Paulo D. Silva,
Renato Vimieiro,
Antônia Sônia Cardoso Diniz:
Optimization of Neural Network's Training Sets via Clustering: Application in Solar Collector Representation.
ICEIS (2) 2004: 147-152 |
2 | EE | Luis E. Zárate,
Elizabeth Marques Duarte Pereira,
João Paulo D. Silva,
Renato Vimieiro,
Antônia Sônia Cardoso Diniz:
Neural Representation of a Solar Collector with Statistical Optimization of the Training Set.
IEA/AIE 2004: 87-96 |
2000 |
1 | EE | Luis E. Zárate:
A Model for the Simulation of a Cold Rolling Mill, Using Neural Networks and Sensitivity Factors.
SBRN 2000: 185-190 |