J. C. Nievola

发表

Discovering Fuzzy Classification Rules with Genetic Programming and Co-evolution

Alex Alves Freitas, Júlio C. Nievola, Roberto R. F. Mendes, 2001, PKDD.

Fuzzy-NNARX based Tool for Monitoring and Predicting Patients Conditions using Selected Vital Signs

Cecilia H. Vallejos de Schatz, P. J. Abatti, J. C. Nievola, 2015 .

TECHNOLOGY IN HEALTH: KNOWLEDGE DISCOVERY IN PUBLIC HEALTH DATABASES: STUDY OF VIRAL HEPATITIS IN THE STATE OF PARANÁ, BRAZIL

S. J. Moysés, J. C. Nievola, C. Moro, 2012 .

A Key Risk Indicator for the Game Usage Lifecycle

Júlio C. Nievola, Emerson Cabrera Paraiso, Luiz Kummer, 2017, FLAIRS Conference.

Digital Game Usage Lifecycle: a systematic literature review

J. C. Nievola, E. Paraiso, L. Kummer, 2018 .

k-Nearest Neighbor Regression in the Estimation of Tectona Grandis Trunk Volume in the State of Pará, Brazil

C. Sanquetta, A. Corte, J. C. Nievola, 2019, Journal of Sustainable Forestry.

k-NEAREST NEIGHBOR AND LINEAR REGRESSION IN THE PREDICTION OF THE ARTIFICIAL FORM FACTOR

C. Sanquetta, A. Corte, J. C. Nievola, 2020 .

RCMDE-GSD: BUILDING GLOBAL HIERARCHICAL CLASSIFIERS USING DIFFERENTIAL EVOLUTION FOR PREDICTING GENE ONTOLOGY TERMS

J. C. Nievola, R. A. Menezes, 2014 .

Local Hierarchical Classification Techniques Analysis Using Attribute Selection for Protein Function Prediction

J. C. Nievola, Leonardo Henrique Pereira, Carlos Nascimento Silla Junior, 2019, 2019 International Conference on Computational Science and Computational Intelligence (CSCI).

Prediction of the occurrence of leprosy reactions based on Bayesian networks

M. Olandoski, M. A. Pontes, H. Gonçalves, 2022, Frontiers in medicine.

Classifying Hierarchical Data Streams using Global Classifiers and Summarization Techniques

J. P. Barddal, J. C. Nievola, Eduardo Tieppo, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

Automatic disease vector mosquitoes identification via hierarchical data stream classification

J. P. Barddal, J. C. Nievola, Eduardo Tieppo, 2022, SAC.

Adaptive Global k-Nearest Neighbors for Hierarchical Classification of Data Streams*

J. P. Barddal, J. C. Nievola, Eduardo Tieppo, 2021, 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

THIAGO BASSANI DESIGN OF A BCI SYSTEM USING EEG SIGNAL ANALYSIS WITH CONTINUOUS WAVELET TRANSFORMATION AND NAÏVES BAYES CLASSIFIER

J. C. Nievola, Cesar Nievola, 2009 .

Improving Data Stream Classification using Incremental Yeo-Johnson Power Transformation

J. P. Barddal, J. C. Nievola, Eduardo Tieppo, 2022, 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Multiobjective Optimization of Indexes Obtained by Clustering for Feature Selection Methods Evaluation in Genes Expression Microarrays

Júlio C. Nievola, Emerson Cabrera Paraiso, Rodolfo Garcia, 2011, IDEAL.

Gene Selection from Microarray Data

Júlio C. Nievola, Helyane Bronoski Borges, J. C. Nievola, 2009, Intelligent Text Categorization and Clustering.

Automatic Classification of Processes in a General-Purpose Operating System

Júlio C. Nievola, Carlos Maziero, Priscila Vriesman Araujo, 2011, 2011 Brazilian Symposium on Computing System Engineering.

Gene-finding as an Attribute Selection Task

Júlio C. Nievola, Helyane Bronoski Borges, J. C. Nievola, 2007, 6th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007).

Attribute selection methods comparison for classification of diffuse large B-cell lymphoma

Júlio C. Nievola, Helyane Bronoski Borges, J. C. Nievola, 2005, Fourth International Conference on Machine Learning and Applications (ICMLA'05).

A constructive algorithm for neural networks inspired on decision trees and evolutionary algorithms

Júlio C. Nievola, Emerson Cabrera Paraiso, Marcus Vinícius Mazega Figueredo, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

[Data mining and characteristics of infant mortality].

Julio Cesar Nievola, Samuel Jorge Moysés, S. J. Moysés, 2010, Cadernos de saude publica.

Hierarchical classification of data streams: a systematic literature review

J. P. Barddal, J. C. Nievola, Eduardo Tieppo, 2021, Artificial Intelligence Review.

Facial expression recognition using a pairwise feature selection and classification approach

Alessandro Lameiras Koerich, Alessandro L. Koerich, Júlio C. Nievola, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Suicide mortality among youth in southern Brazil: a spatiotemporal evaluation of socioeconomic vulnerability

J. Vissoci, Elias C A Carvalho, C. Staton, 2019, Revista brasileira de psiquiatria.

Classifying Potentially Unbounded Hierarchical Data Streams with Incremental Gaussian Naive Bayes

Jean Paul Barddal, Eduardo Tieppo, Júlio Cesar Nievola, 2021, BRACIS.

A generalized financial time series forecasting model based on automatic feature engineering using genetic algorithms and support vector machine

Júlio C. Nievola, Norberto Ritzmann Junior, J. C. Nievola, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Pattern recognition for brain-computer interface on disabled subjects using a wavelet transformation

Júlio C. Nievola, Thiago Bassani, J. C. Nievola, 2008, 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

An Adaptive Approach for Index Tuning with Learning Classifier Systems on Hybrid Storage Environments

Júlio C. Nievola, Wendel Góes Pedrozo, Deborah Carvalho Ribeiro, 2018, HAIS.

Dynamic Fuzzy-Neural based tool formonitoring and predicting patients conditions using selected vital signs

Júlio C. Nievola, Paulo José Abatti, Cecilia H. Vallejos de Schatz, 2015, J. Intell. Fuzzy Syst..

An evaluation of global-model hierarchical classification algorithms for hierarchical classification problems with single path of labels

Júlio C. Nievola, Helyane Bronoski Borges, Carlos Nascimento Silla, 2013, Comput. Math. Appl..

Applying Commitment to Churn and Remaining Players Lifetime Prediction

Júlio C. Nievola, Emerson Cabrera Paraiso, Luiz Bernardo Martins Kummer, 2018, 2018 IEEE Conference on Computational Intelligence and Games (CIG).

Multi-Label Hierarchical Classification for Protein Function Prediction

Julio Cesar Nievola, Helyane Bronoski Borges, J. C. Nievola, 2013 .

Multi-Label Hierarchical Classification using a Competitive Neural Network for protein function prediction

Júlio C. Nievola, Helyane Bronoski Borges, J. C. Nievola, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Hierarchical classification using a Competitive Neural Network

Júlio C. Nievola, Helyane Bronoski Borges, J. C. Nievola, 2012, 2012 8th International Conference on Natural Computation.

A Centroid-based Approach for Hierarchical Classification

Fabrício Enembreck, Júlio C. Nievola, Bráulio Coelho Ávila, 2015, ICEIS.

Using Neural Network Rule Extraction for Credit-Risk Evaluation

Maria Teresinha Arns Steiner, Nei Yoshihiro Soma, Tamio Shimizu, 2006 .

New models for long-term Internet traffic forecasting using artificial neural networks and flow based information

Júlio C. Nievola, Marcelo Eduardo Pellenz, Manoel Camillo Penna, 2012, 2012 IEEE Network Operations and Management Symposium.

Predicting GPCR and enzymes function with a global approach based on LCS

Júlio C. Nievola, Luiz Melo Romão, J. C. Nievola, 2012, 2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE).

Predicting published news effect in the Brazilian stock market

Júlio C. Nievola, P. S. M. Nizer, J. C. Nievola, 2012, Expert Syst. Appl..

Evaluation of the Relevance of Linear and Nonlinear Posturographic Features in the Recognition of Healthy Subjects and Stroke Patients

Júlio C. Nievola, Luiz Henrique Giovanini Marrega, J. C. Nievola, 2014, 2014 IEEE International Conference on Data Mining Workshop.

Sampling and Digital Filtering Effects When Recognizing Postural Control with Statistical Tools and the Decision Tree Classifier

Luiz Henrique Giovanini Giovanini, Simone M. Silva, Elisangela F. Manffra, 2017, ICCS.

Using a Genetic Algorithm Approach to Study the Impact of Imbalanced Corpora in Sentiment Analysis

Júlio C. Nievola, Emerson Cabrera Paraiso, Lohann Ferreira, 2015, FLAIRS.

Extracting comprehensible rules from neural networks via genetic algorithms

Alex A. Freitas, Julio Cesar Nievola, R. T. Santos, 2000, 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks. Proceedings of the First IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (Cat. No.00.

BNPA: An R package to learn path analysis input models from a data set semi-automatically using Bayesian networks

Júlio C. Nievola, Emerson Cabrera Paraiso, Joao Ricardo Nickenig Vissoci, 2021, Knowl. Based Syst..

Noctua: A tool for Knowledge Acquisition and Collaborative Knowledge Construction with a virtual catalyst

Júlio C. Nievola, Milton Pires Ramos, Gilson Yukio Sato, 2011, Proceedings of the 2011 15th International Conference on Computer Supported Cooperative Work in Design (CSCWD).

A Virtual Catalyst in the Knowledge Acquisition Process

Júlio C. Nievola, Cesar Augusto Tacla, Milton Pires Ramos, 2011, SEKE.

Comparative Study of Dimensionality Reduction Methods Using Reliable Features for Multiple Datasets Obtained by rs-fMRI in ADHD Prediction

Júlio C. Nievola, Emerson Cabrera Paraiso, Rodolfo Garcia, 2017, Canadian Conference on AI.

Genetic Programming for Attribute Construction in Data Mining

Fernando E. B. Otero, Monique M. S. Silva, Alex A. Freitas, 2002, EuroGP.

Dynamically modeling users with MODUS-SD and Kohonen's map

Júlio C. Nievola, Milton Pires Ramos, Emerson Cabrera Paraiso, 2013, Proceedings of the 2013 IEEE 17th International Conference on Computer Supported Cooperative Work in Design (CSCWD).

Brain-computer interface using wavelet transformation and naïve bayes classifier.

Thiago Bassani, Julio Cesar Nievola, J. C. Nievola, 2010, Advances in experimental medicine and biology.

Knowledge-Based Systems

J. C. Nievola, E. Paraiso, Elias César Araújo de Carvalho, 2021 .