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ORCIDPyramo Pires da Costa Jr.
2010 – 2019
- 2013
[j2]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
- [j1]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) - [c11]Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving granular neural network for fuzzy time series forecasting. IJCNN 2012: 1-8 - 2011
- [c10]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
- [c9]Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving granular neural network for semi-supervised data stream classification. IJCNN 2010: 1-8 - [c8]Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide:
Granular Approach for Evolving System Modeling. IPMU 2010: 340-349
2000 – 2009
- 2009
- [c7]Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide:
Evolving granular classification neural networks. IJCNN 2009: 1736-1743 - 2008
- [c6]Michel Hell, Pyramo Costa Jr., Fernando A. C. Gomide:
Hybrid neurofuzzy computing with nullneurons. IJCNN 2008: 3653-3659 - [c5]Michel Hell, Fernando A. C. Gomide, Pyramo Costa Jr.:
Neurons and Neural Fuzzy Networks Based on Nullnorms. SBRN 2008: 123-128 - 2007
- [c4]Michel Hell, Rosangela Ballini, Pyramo Costa Jr., Fernando A. C. Gomide:
Training Neurofuzzy Networks with Participatory Learning. EUSFLAT Conf. (2) 2007: 231-236 - [c3]Michel Hell, Pyramo Costa Jr., Fernando A. C. Gomide:
New Neurofuzzy Training Procedure Based on Participatory Learning Paradigm. FUZZ-IEEE 2007: 1-6 - 2005
- [c2]Délio E. B. Fernandes, Mário Fabiano Alves, Pyramo Pires da Costa Jr.:
A Voltage Sag Pattern Classification Technique. PReMI 2005: 248-253 - [c1]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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