F. M. Varejão

发表

Uma Abordagem com Multi-Mochilas Multidimensionais para o Problema de Alocação de Ações de Redução de Perdas na Distribuição de Energia

A. C. B. Delbem, F. M. Varejão, A.R.S. Amaral, 2015 .

A novel cooperative algorithm for clustering large databases using sampling

F. M. Varejão, Alexandre L. Rodrigues, F. Fabris, 2012 .

Politecnico di Torino Porto Institutional Repository [ Proceeding ] A multi-measure nearest neighbor algorithm for time series classification

F. M. Varejão, F. Fabris, I. Drago, 2017 .

HYBRID GENETIC ALGORITHM APPLIED TO THE CLUSTERING PROBLEM

Flávio Miguel Varejão, F. M. Varejão, Danuza Prado de Faria, 2012 .

Feature Extraction and Selection for Automatic Fault Diagnosis of Rotating Machinery

Thomas W. Rauber, F. M. Varejão, F. D. A. Boldt, 2013 .

Metric Learning for Electrical Submersible Pump Fault Diagnosis

Flávio Miguel Varejão, Marcos Pellegrini Ribeiro, Alexandre Rodrigues Loureiros, 2020, IJCNN.

Model-free Motor Pump Fault Diagnosis Using Automatic Feature Model Generation

F. M. Varejão, T. Rauber, E. Mendel, 2011 .

An experimental framework for evaluating loss minimization in multi‐label classification via stochastic process

F. M. Varejão, Alexandre L. Rodrigues, L. H. S. Mello, 2022, Comput. Intell..

On Classes and Costs of Multimodal Interfaces

Raquel Oliveira Prates, F. M. Varejão, R. Prates, 2007 .

Deep Learning Intelligent Fault Diagnosis of Electrical Submersible Pump Based on Raw Time Domain Vibration Signals

F. M. Varejão, Thiago Oliveira-Santos, L. H. S. Mello, 2022, 2022 IEEE 31st International Symposium on Industrial Electronics (ISIE).

Active learning for new-fault class sample recovery in electrical submersible pump fault diagnosis

Lucas Henrique Sousa Mello, F. M. Varejão, Thiago Oliveira-Santos, 2022, Expert Syst. Appl..

Integrating search methods on Active Documents

F. M. Varejão, Maria Ester Soares Xavier, 2003 .

Ensemble of classifier chains and decision templates for multi-label classification

F. M. Varejão, M. Segatto, Victor Freitas Rocha, 2022, Knowledge and Information Systems.

An experimental methodology to evaluate machine learning methods for fault diagnosis based on vibration signals

Francisco de Assis Boldt, Flávio Miguel Varejão, Thomas W. Rauber, 2020, Expert Syst. Appl..

Sampling approaches for applying DBSCAN to large datasets

Flávio Miguel Varejão, Diego Luchi, F. M. Varejão, 2019, Pattern Recognit. Lett..

A methodology to refine the technical losses calculation from estimates of non-technical losses

Giovanni Comarela, Flávio Miguel Varejão, F. M. Varejão, 2009 .

Using GA for the stratified sampling of electricity consumers

Flávio Miguel Varejão, E. de O. da Costa, Fábio Fabris, 2013, 2013 IEEE Congress on Evolutionary Computation.

Optimization metaheuristics for minimizing variance in a real-world statistical application

Flávio Miguel Varejão, Fábio Fabris, Alexandre Rodrigues Loureiros, 2013, SAC '13.

Pattern Recognition based Fault Diagnosis in Industrial Processes: Review and Application

Thomas W. Rauber, Flávio Miguel Varejão, Estefhan Dazzi Wandekokem, 2010 .

Reducing power companies billing costs via empirical bayes and seasonality remover

Vítor Estêvão Silva Souza, Flávio Miguel Varejão, Thiago Oliveira-Santos, 2019, Eng. Appl. Artif. Intell..

Cascade Feature Selection and ELM for automatic fault diagnosis of the Tennessee Eastman process

Thomas W. Rauber, Francisco de Assis Boldt, Flávio Miguel Varejão, 2017, Neurocomputing.

Evaluation of the Extreme Learning Machine for automatic fault diagnosis of the Tennessee Eastman chemical process

Thomas W. Rauber, Francisco de Assis Boldt, Flávio Miguel Varejão, 2014, IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society.

Heterogeneous Feature Models and Feature Selection Applied to Bearing Fault Diagnosis

Thomas W. Rauber, Francisco de Assis Boldt, Flávio Miguel Varejão, 2015, IEEE Transactions on Industrial Electronics.

Motor Pump Fault Diagnosis with Feature Selection and Levenberg-Marquardt Trained Feedforward Neural Network

Thomas W. Rauber, Flávio Miguel Varejão, F. M. Varejão, 2013, CAIP.

Flow Instability Detection in Offshore Oil Wells with Multivariate Time Series Machine Learning Classifiers

Flávio Miguel Varejão, Ricardo Menezes Salgado, F. M. Varejão, 2021, 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE).

Performance evaluation of a sensor-based system devised to minimize commercial losses in street lighting networks

Henrique A. C. Braga, Flávio Miguel Varejão, Guilherme Marcio Soares, 2014, 2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings.

Automated image recognition of public lighting luminaries

Flávio Miguel Varejão, José Gonçalves Pereira Filho, R. S. Broetto, 2013, 2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS).

Single Sequence Fast Feature Selection for High-Dimensional Data

Thomas W. Rauber, Francisco de Assis Boldt, Flávio Miguel Varejão, 2015, 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI).

BIRCHSCAN: A sampling method for applying DBSCAN to large datasets

Flávio Miguel Varejão, Diego Luchi, F. M. Varejão, 2021, Expert Syst. Appl..

Monthly energy consumption forecast: A deep learning approach

Flávio Miguel Varejão, Rodrigo Ferreira Berriel, Thiago Oliveira-Santos, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Performance analysis of extreme learning machine for automatic diagnosis of electrical submersible pump conditions

Thomas W. Rauber, Francisco de Assis Boldt, Flávio Miguel Varejão, 2014, 2014 12th IEEE International Conference on Industrial Informatics (INDIN).

HyperADD: An Incremental and Hybrid Approach for Knowledge Acquisition on Active Design Documents

Ana Cristina Bicharra Garcia, Flávio Miguel Varejão, F. M. Varejão, 2000, FLAIRS.

Fast feature selection using hybrid ranking and wrapper approach for automatic fault diagnosis of motorpumps based on vibration signals

Thomas W. Rauber, Francisco de Assis Boldt, Flávio Miguel Varejão, 2015, 2015 IEEE 13th International Conference on Industrial Informatics (INDIN).

A fast feature selection algorithm applied to automatic faults diagnosis of rotating machinery

Thomas W. Rauber, Francisco de Assis Boldt, Flávio Miguel Varejão, 2013 .

Computational intelligence for automatic diagnosis of submersible motor pump conditions in offshore oil exploration

Thomas W. Rauber, Francisco de Assis Boldt, Flávio Miguel Varejão, 2013, 2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS).

A Domain-Specific Language for Fault Diagnosis in Electrical Submersible Pumps

Vítor Estêvão Silva Souza, Flávio Miguel Varejão, Marcos Pellegrini Ribeiro, 2018, 2018 IEEE 16th International Conference on Industrial Informatics (INDIN).

Genetic Sampling k-means for Clustering Large Data Sets

Flávio Miguel Varejão, Alexandre Rodrigues Loureiros, Diego Luchi, 2015, CIARP.

Ensemble of metric learners for improving electrical submersible pump fault diagnosis

F. M. Varejão, Thiago Oliveira-Santos, L. H. S. Mello, 2022, Journal of Petroleum Science and Engineering.