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Pyramo Pires da Costa Jr.

Pyramo Costa Jr.

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affiliation: Pontifical Catholic University of Minas Gerais, Graduate Program in Electrical Engineering

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2010 – 2019

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2013
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Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving granular neural networks from fuzzy data streams. Neural Networks 38: 1-16 (2013)
2012
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Daniel F. Leite, Rosangela Ballini, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving fuzzy granular modeling from nonstationary fuzzy data streams. Evol. Syst. 3(2): 65-79 (2012)
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  - conf/ijcnn/LeiteCG12
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Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving granular neural network for fuzzy time series forecasting. IJCNN 2012: 1-8
2011
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Daniel F. Leite, Fernando A. C. Gomide, Rosangela Ballini, Pyramo Costa Jr.:
Fuzzy granular evolving modeling for time series prediction. FUZZ-IEEE 2011: 2794-2801
2010
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Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving granular neural network for semi-supervised data stream classification. IJCNN 2010: 1-8
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Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide:
Granular Approach for Evolving System Modeling. IPMU 2010: 340-349

2000 – 2009

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2009
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Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving granular classification neural networks. IJCNN 2009: 1736-1743
2008
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Michel Hell, Pyramo Costa Jr., Fernando A. C. Gomide:
Hybrid neurofuzzy computing with nullneurons. IJCNN 2008: 3653-3659
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Michel Hell, Fernando A. C. Gomide, Pyramo Costa Jr.:
Neurons and Neural Fuzzy Networks Based on Nullnorms. SBRN 2008: 123-128
2007
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Michel Hell, Rosangela Ballini, Pyramo Costa Jr., Fernando A. C. Gomide:
Training Neurofuzzy Networks with Participatory Learning. EUSFLAT Conf. (2) 2007: 231-236
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Michel Hell, Pyramo Costa Jr., Fernando A. C. Gomide:
New Neurofuzzy Training Procedure Based on Participatory Learning Paradigm. FUZZ-IEEE 2007: 1-6
2005
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Délio E. B. Fernandes, Mário Fabiano Alves, Pyramo Pires da Costa Jr.:
A Voltage Sag Pattern Classification Technique. PReMI 2005: 248-253
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Michel Hell, Luiz Secco, Pyramo Costa Jr., Fernando A. C. Gomide:
Recurrent Neural Approaches for Power Transformers Thermal Modeling. PReMI 2005: 287-293

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