Nelson F. F. Ebecken
Nelson F. F. Ebecken
Professor of Computational Systems
Verified email at - Homepage
Cited by
Cited by
A genetic algorithm for cluster analysis
ER Hruschka, NFF Ebecken
Intelligent data analysis 7 (1), 15-25, 2003
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
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
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
Extracting rules from multilayer perceptrons in classification problems: A clustering-based approach
ER Hruschka, NFF Ebecken
Neurocomputing 70 (1-3), 384-397, 2006
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
Fault-tree analysis: a knowledge-engineering approach
JAB Geymayr, NFF Ebecken
IEEE Transactions on Reliability 44 (1), 37-45, 1995
Bayesian networks for imputation in classification problems
ER Hruschka, ER Hruschka, NFF Ebecken
Journal of Intelligent Information Systems 29, 231-252, 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
FuzzyFTA: a fuzzy fault tree system for uncertainty analysis
ACF Guimarẽes, NFF Ebecken
Annals of Nuclear Energy 26 (6), 523-532, 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
Towards efficient variables ordering for Bayesian networks classifier
ER Hruschka Jr, NFF Ebecken
Data & Knowledge Engineering 63 (2), 258-269, 2007
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
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
Mineração de textos
NFF Ebecken, MCS Lopes, MCA COSTA
Sistemas inteligentes: fundamentos e aplicações. São Carlos: Manole, 337-370, 2003
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
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
Feature selection by Bayesian networks
ER Hruschka, ER Hruschka, NFF Ebecken
Advances in Artificial Intelligence: 17th Conference of the Canadian Society …, 2004
Knowledge discovering for coastal waters classification
GC Pereira, NFF Ebecken
Expert Systems with Applications 36 (4), 8604-8609, 2009
Evaluating a nearest-neighbor method to substitute continuous missing values
ER Hruschka, ER Hruschka Jr, NFF Ebecken
Australasian Joint Conference on Artificial Intelligence, 723-734, 2003
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