| A genetic algorithm for cluster analysis ER Hruschka, NFF Ebecken Intelligent data analysis 7 (1), 15-25, 2003 | 193 | 2003 |
| A KNN undersampling approach for data balancing M Beckmann, NFF Ebecken, BSLP De Lima Journal of Intelligent Learning Systems and Applications 7 (4), 104-116, 2015 | 160 | 2015 |
| On extending f-measure and g-mean metrics to multi-class problems RP Espíndola, NFF Ebecken WIT Transactions on Information and Communication Technologies 35, 25-34, 2005 | 155 | 2005 |
| Optimization of mass concrete construction using genetic algorithms EMR Fairbairn, MM Silvoso, RD Toledo Filho, JLD Alves, NFF Ebecken Computers & structures 82 (2-3), 281-299, 2004 | 137 | 2004 |
| Sugarcane yield prediction in Brazil using NDVI time series and neural networks ensemble JL Fernandes, NFF Ebecken, JCDM Esquerdo International journal of remote sensing 38 (16), 4631-4644, 2017 | 129 | 2017 |
| Extracting rules from multilayer perceptrons in classification problems: A clustering-based approach ER Hruschka, NFF Ebecken Neurocomputing 70 (1-3), 384-397, 2006 | 120 | 2006 |
| Fault-tree analysis: a knowledge-engineering approach JAB Geymayr, NFF Ebecken IEEE Transactions on Reliability 44 (1), 37-45, 1995 | 111 | 1995 |
| Bayesian networks for imputation in classification problems ER Hruschka, ER Hruschka, NFF Ebecken Journal of Intelligent Information Systems 29, 231-252, 2007 | 100 | 2007 |
| Evaluating the correlation between objective rule interestingness measures and real human interest DR Carvalho, AA Freitas, N Ebecken Knowledge Discovery in Databases: PKDD 2005: 9th European Conference on …, 2005 | 81 | 2005 |
| FuzzyFTA: a fuzzy fault tree system for uncertainty analysis ACF Guimarẽes, NFF Ebecken Annals of Nuclear Energy 26 (6), 523-532, 1999 | 80 | 1999 |
| An optimized implementation of the Newmark/Newton‐Raphson algorithm for the time integration of non‐linear problems BP Jacob, NFF Ebecken Communications in Numerical Methods in Engineering 10 (12), 983-992, 1994 | 79 | 1994 |
| Towards efficient variables ordering for Bayesian networks classifier ER Hruschka Jr, NFF Ebecken Data & Knowledge Engineering 63 (2), 258-269, 2007 | 71 | 2007 |
| Neural network model to predict a storm surge MMF De Oliveira, NFF Ebecken, JLF De Oliveira, I de Azevedo Santos Journal of applied Meteorology and Climatology 48 (1), 143-155, 2009 | 70 | 2009 |
| A comparison of models for uncertainty analysis by the finite element method BSLP de Lima, NFF Ebecken Finite Elements in Analysis and Design 34 (2), 211-232, 2000 | 69 | 2000 |
| Mineração de textos NFF Ebecken, MCS Lopes, MCA COSTA Sistemas inteligentes, 337-370, 2003 | 59 | 2003 |
| Feature selection by Bayesian networks ER Hruschka, ER Hruschka, NFF Ebecken Advances in Artificial Intelligence: 17th Conference of the Canadian Society …, 2004 | 52 | 2004 |
| Determination of probabilistic parameters of concrete: solving the inverse problem by using artificial neural networks EMR Fairbairn, NFF Ebecken, CNM Paz, FJ Ulm Computers & Structures 78 (1-3), 497-503, 2000 | 49 | 2000 |
| A tecnologia de realidade virtual como recurso para formação em saúde pública à distância: uma aplicação para a aprendizagem dos procedimentos antropométricos ECVC Barilli, NFF Ebecken, GG Cunha Ciência & Saúde Coletiva 16, 1247-1256, 2011 | 48* | 2011 |
| Growing compact RBF networks using a genetic algorithm AMS Barreto, HJC Barbosa, NFF Ebecken VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings., 61-66, 2002 | 47 | 2002 |
| A survey on video detection and tracking of maritime vessels RDS Moreira, NFF Ebecken, AS Alves, F Livernet, A Campillo-Navetti International Journal of Recent Research and Applied Studies 20 (1), 2014 | 46 | 2014 |
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