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Trabalho de evento-anais periodico
Sequential short-text classification from multiple textual representations with weak supervision (2022)
Reis Filho, Ivan José ; Martins, Luiz Henrique Dutra ; Parmezan, Antonio Rafael Sabino ; Marcacini, Ricardo Marcondes ; Rezende, Solange Oliveira
Source: Lecture Notes in Artificial Intelligence. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE TEXTO, MINERAÇÃO DE DADOS, ANÁLISE DE SÉRIES TEMPORAIS
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ABNT
REIS FILHO, Ivan José et al. Sequential short-text classification from multiple textual representations with weak supervision. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-21686-2_12. Acesso em: 16 nov. 2024. , 2022
APA
Reis Filho, I. J., Martins, L. H. D., Parmezan, A. R. S., Marcacini, R. M., & Rezende, S. O. (2022). Sequential short-text classification from multiple textual representations with weak supervision. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-21686-2_12
NLM
Reis Filho IJ, Martins LHD, Parmezan ARS, Marcacini RM, Rezende SO. Sequential short-text classification from multiple textual representations with weak supervision [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 165-179.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_12
Vancouver
Reis Filho IJ, Martins LHD, Parmezan ARS, Marcacini RM, Rezende SO. Sequential short-text classification from multiple textual representations with weak supervision [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 165-179.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_12
Trabalho de evento-anais periodico
Time-series in hyper-parameter initialization of machine learning techniques (2021)
Horváth, Tomás ; Mantovani, Rafael Gomes ; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Lecture Notes in Computer Science. Conference titles: International Conference on Intelligent Data Engineering and Automated Learning - IDEAL. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, COMPONENTES PRINCIPAIS, ANÁLISE DE SÉRIES TEMPORAIS
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ABNT
HORVÁTH, Tomás e MANTOVANI, Rafael Gomes e CARVALHO, André Carlos Ponce de Leon Ferreira de. Time-series in hyper-parameter initialization of machine learning techniques. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-91608-4_25. Acesso em: 16 nov. 2024. , 2021
APA
Horváth, T., Mantovani, R. G., & Carvalho, A. C. P. de L. F. de. (2021). Time-series in hyper-parameter initialization of machine learning techniques. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-030-91608-4_25
NLM
Horváth T, Mantovani RG, Carvalho ACP de LF de. Time-series in hyper-parameter initialization of machine learning techniques [Internet]. Lecture Notes in Computer Science. 2021 ; 13113 246-258.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-91608-4_25
Vancouver
Horváth T, Mantovani RG, Carvalho ACP de LF de. Time-series in hyper-parameter initialization of machine learning techniques [Internet]. Lecture Notes in Computer Science. 2021 ; 13113 246-258.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-91608-4_25
Trabalho de evento-anais periodico
Evaluate pseudo labeling and CNN for multi-variate time series classification in low-data regimes (2021)
Ienco, Dino ; Pereira-Santos, Davi; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Lecture Notes in Computer Science. Conference titles: International Conference on Artificial Neural Networks - ICANN. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, REDES NEURAIS, APRENDIZADO COMPUTACIONAL
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ABNT
IENCO, Dino e PEREIRA-SANTOS, Davi e CARVALHO, André Carlos Ponce de Leon Ferreira de. Evaluate pseudo labeling and CNN for multi-variate time series classification in low-data regimes. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-86383-8_10. Acesso em: 16 nov. 2024. , 2021
APA
Ienco, D., Pereira-Santos, D., & Carvalho, A. C. P. de L. F. de. (2021). Evaluate pseudo labeling and CNN for multi-variate time series classification in low-data regimes. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-030-86383-8_10
NLM
Ienco D, Pereira-Santos D, Carvalho ACP de LF de. Evaluate pseudo labeling and CNN for multi-variate time series classification in low-data regimes [Internet]. Lecture Notes in Computer Science. 2021 ; 12895 126-137.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-86383-8_10
Vancouver
Ienco D, Pereira-Santos D, Carvalho ACP de LF de. Evaluate pseudo labeling and CNN for multi-variate time series classification in low-data regimes [Internet]. Lecture Notes in Computer Science. 2021 ; 12895 126-137.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-86383-8_10
Trabalho de evento-anais periodico
A fuzzy approach for classification and novelty detection in data streams under intermediate latency (2020)
Cristiani, André Luis ; Silva, Tiago Pinho da ; Camargo, Heloisa de Arruda
Source: Lecture Notes in Artificial Intelligence. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, FUZZY (INTELIGÊNCIA ARTIFICIAL), RECONHECIMENTO DE PADRÕES, ANÁLISE DE SÉRIES TEMPORAIS
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ABNT
CRISTIANI, André Luis e SILVA, Tiago Pinho da e CAMARGO, Heloisa de Arruda. A fuzzy approach for classification and novelty detection in data streams under intermediate latency. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-61380-8_12. Acesso em: 16 nov. 2024. , 2020
APA
Cristiani, A. L., Silva, T. P. da, & Camargo, H. de A. (2020). A fuzzy approach for classification and novelty detection in data streams under intermediate latency. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-61380-8_12
NLM
Cristiani AL, Silva TP da, Camargo H de A. A fuzzy approach for classification and novelty detection in data streams under intermediate latency [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 171-186.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_12
Vancouver
Cristiani AL, Silva TP da, Camargo H de A. A fuzzy approach for classification and novelty detection in data streams under intermediate latency [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 171-186.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_12
Trabalho de evento-anais periodico
Quantifying temporal novelty in social networks using time-varying graphs and concept drift detection (2020)
Santos, Victor M. G. dos; Mello, Rodrigo Fernandes de ; Nogueira, Tatiane ; Rios, Ricardo A
Source: Lecture Notes in Artificial Intelligence. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, ANÁLISE DE SÉRIES TEMPORAIS, MÍDIAS SOCIAIS
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ABNT
SANTOS, Victor M. G. dos et al. Quantifying temporal novelty in social networks using time-varying graphs and concept drift detection. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-61380-8_44. Acesso em: 16 nov. 2024. , 2020
APA
Santos, V. M. G. dos, Mello, R. F. de, Nogueira, T., & Rios, R. A. (2020). Quantifying temporal novelty in social networks using time-varying graphs and concept drift detection. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-61380-8_44
NLM
Santos VMG dos, Mello RF de, Nogueira T, Rios RA. Quantifying temporal novelty in social networks using time-varying graphs and concept drift detection [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 650-664.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_44
Vancouver
Santos VMG dos, Mello RF de, Nogueira T, Rios RA. Quantifying temporal novelty in social networks using time-varying graphs and concept drift detection [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 650-664.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_44
Trabalho de evento-anais periodico
2CS: correlation-guided split candidate selection in Hoeffding tree regressors (2020)
Mastelini, Saulo Martiello ; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Lecture Notes in Artificial Intelligence. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS, ALGORITMOS ÚTEIS E ESPECÍFICOS
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ABNT
MASTELINI, Saulo Martiello e CARVALHO, André Carlos Ponce de Leon Ferreira de. 2CS: correlation-guided split candidate selection in Hoeffding tree regressors. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-61380-8_23. Acesso em: 16 nov. 2024. , 2020
APA
Mastelini, S. M., & Carvalho, A. C. P. de L. F. de. (2020). 2CS: correlation-guided split candidate selection in Hoeffding tree regressors. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-61380-8_23
NLM
Mastelini SM, Carvalho ACP de LF de. 2CS: correlation-guided split candidate selection in Hoeffding tree regressors [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 337-351.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_23
Vancouver
Mastelini SM, Carvalho ACP de LF de. 2CS: correlation-guided split candidate selection in Hoeffding tree regressors [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 337-351.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_23
Trabalho de evento-anais periodico
Data streams are time series: challenging assumptions (2020)
Read, Jesse ; Rios, Ricardo A ; Nogueira, Tatiane ; Mello, Rodrigo Fernandes de
Source: Lecture Notes in Artificial Intelligence. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS
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ABNT
READ, Jesse et al. Data streams are time series: challenging assumptions. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-61380-8_36. Acesso em: 16 nov. 2024. , 2020
APA
Read, J., Rios, R. A., Nogueira, T., & Mello, R. F. de. (2020). Data streams are time series: challenging assumptions. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-61380-8_36
NLM
Read J, Rios RA, Nogueira T, Mello RF de. Data streams are time series: challenging assumptions [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 529-543.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_36
Vancouver
Read J, Rios RA, Nogueira T, Mello RF de. Data streams are time series: challenging assumptions [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 529-543.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_36
Trabalho de evento-anais periodico
A fuzzy classifier for data streams with infinitely delayed labels (2019)
Silva, Tiago Pinho da; Souza, Vinícius M. A; Batista, Gustavo Enrique de Almeida Prado Alves; Camargo, Heloisa de Arruda
Source: Lecture Notes in Computer Science. Conference titles: Iberoamerican Congress on Pattern Recognition - CIARP : Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, FUZZY (INTELIGÊNCIA ARTIFICIAL)
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ABNT
SILVA, Tiago Pinho da et al. A fuzzy classifier for data streams with infinitely delayed labels. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-13469-3_34. Acesso em: 16 nov. 2024. , 2019
APA
Silva, T. P. da, Souza, V. M. A., Batista, G. E. de A. P. A., & Camargo, H. de A. (2019). A fuzzy classifier for data streams with infinitely delayed labels. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-030-13469-3_34
NLM
Silva TP da, Souza VMA, Batista GE de APA, Camargo H de A. A fuzzy classifier for data streams with infinitely delayed labels [Internet]. Lecture Notes in Computer Science. 2019 ; 11401 314-322.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-13469-3_34
Vancouver
Silva TP da, Souza VMA, Batista GE de APA, Camargo H de A. A fuzzy classifier for data streams with infinitely delayed labels [Internet]. Lecture Notes in Computer Science. 2019 ; 11401 314-322.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-13469-3_34
Trabalho de evento-anais periodico
Towards hierarchical classification of data streams (2019)
Parmezan, Antonio Rafael Sabino; Souza, Vinícius M. A; Batista, Gustavo Enrique de Almeida Prado Alves
Source: Lecture Notes in Computer Science. Conference titles: Iberoamerican Congress on Pattern Recognition - CIARP : Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, MINERAÇÃO DE DADOS, APRENDIZADO COMPUTACIONAL
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ABNT
PARMEZAN, Antonio Rafael Sabino e SOUZA, Vinícius M. A e BATISTA, Gustavo Enrique de Almeida Prado Alves. Towards hierarchical classification of data streams. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-13469-3_37. Acesso em: 16 nov. 2024. , 2019
APA
Parmezan, A. R. S., Souza, V. M. A., & Batista, G. E. de A. P. A. (2019). Towards hierarchical classification of data streams. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-030-13469-3_37
NLM
Parmezan ARS, Souza VMA, Batista GE de APA. Towards hierarchical classification of data streams [Internet]. Lecture Notes in Computer Science. 2019 ; 11401 314-322.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-13469-3_37
Vancouver
Parmezan ARS, Souza VMA, Batista GE de APA. Towards hierarchical classification of data streams [Internet]. Lecture Notes in Computer Science. 2019 ; 11401 314-322.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-13469-3_37
Trabalho de evento-anais periodico
Ensemble clustering for novelty detection in data streams (2019)
Garcia, Kemilly Dearo ; Faria, Elaine Ribeiro de; Sá, Cláudio Rebelo de ; Mendes-Moreira, João ; Aggarwal, Charu C; Carvalho, André Carlos Ponce de Leon Ferreira de ; Kok, Joost N
Source: Lecture Notes in Artificial Intelligence. Conference titles: International Conference on Discovery Science - DS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS
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ABNT
GARCIA, Kemilly Dearo et al. Ensemble clustering for novelty detection in data streams. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-33778-0_34. Acesso em: 16 nov. 2024. , 2019
APA
Garcia, K. D., Faria, E. R. de, Sá, C. R. de, Mendes-Moreira, J., Aggarwal, C. C., Carvalho, A. C. P. de L. F. de, & Kok, J. N. (2019). Ensemble clustering for novelty detection in data streams. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-33778-0_34
NLM
Garcia KD, Faria ER de, Sá CR de, Mendes-Moreira J, Aggarwal CC, Carvalho ACP de LF de, Kok JN. Ensemble clustering for novelty detection in data streams [Internet]. Lecture Notes in Artificial Intelligence. 2019 ; 11828 460-470.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-33778-0_34
Vancouver
Garcia KD, Faria ER de, Sá CR de, Mendes-Moreira J, Aggarwal CC, Carvalho ACP de LF de, Kok JN. Ensemble clustering for novelty detection in data streams [Internet]. Lecture Notes in Artificial Intelligence. 2019 ; 11828 460-470.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-33778-0_34
Trabalho de evento-anais periodico
Feature-based time series classification for service request opening prediction in the telecom industry (2019)
Pereira, Fabíola Souza Fernandes; Carvalho, André Carlos Ponce de Leon Ferreira de ; Assis, Rafael; Costa, Maxley; Faria, Elaine R ; Julia, Rita Maria Silva; Barcelos, Umberto; Melo, Jony
Source: Lecture Notes in Artificial Intelligence. Conference titles: EPIA Conference on Artificial Intelligence - EPIA. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS, TELECOMUNICAÇÕES
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ABNT
PEREIRA, Fabíola Souza Fernandes et al. Feature-based time series classification for service request opening prediction in the telecom industry. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-30244-3_11. Acesso em: 16 nov. 2024. , 2019
APA
Pereira, F. S. F., Carvalho, A. C. P. de L. F. de, Assis, R., Costa, M., Faria, E. R., Julia, R. M. S., et al. (2019). Feature-based time series classification for service request opening prediction in the telecom industry. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-30244-3_11
NLM
Pereira FSF, Carvalho ACP de LF de, Assis R, Costa M, Faria ER, Julia RMS, Barcelos U, Melo J. Feature-based time series classification for service request opening prediction in the telecom industry [Internet]. Lecture Notes in Artificial Intelligence. 2019 ; 11805 120-132.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-30244-3_11
Vancouver
Pereira FSF, Carvalho ACP de LF de, Assis R, Costa M, Faria ER, Julia RMS, Barcelos U, Melo J. Feature-based time series classification for service request opening prediction in the telecom industry [Internet]. Lecture Notes in Artificial Intelligence. 2019 ; 11805 120-132.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-30244-3_11
Trabalho de evento-anais periodico
Online clustering for novelty detection and concept drift in data streams (2019)
Garcia, Kemilly Dearo; Poel, Mannes ; Kok, Joost N ; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Lecture Notes in Artificial Intelligence. Conference titles: EPIA Conference on Artificial Intelligence - EPIA. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GARCIA, Kemilly Dearo et al. Online clustering for novelty detection and concept drift in data streams. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-30244-3_37. Acesso em: 16 nov. 2024. , 2019
APA
Garcia, K. D., Poel, M., Kok, J. N., & Carvalho, A. C. P. de L. F. de. (2019). Online clustering for novelty detection and concept drift in data streams. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-30244-3_37
NLM
Garcia KD, Poel M, Kok JN, Carvalho ACP de LF de. Online clustering for novelty detection and concept drift in data streams [Internet]. Lecture Notes in Artificial Intelligence. 2019 ; 11805 448-459.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-30244-3_37
Vancouver
Garcia KD, Poel M, Kok JN, Carvalho ACP de LF de. Online clustering for novelty detection and concept drift in data streams [Internet]. Lecture Notes in Artificial Intelligence. 2019 ; 11805 448-459.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-30244-3_37
Trabalho de evento-anais periodico
A cluster-based prototype reduction for online classification (2018)
Garcia, Kemilly Dearo; Carvalho, André Carlos Ponce de Leon Ferreira de ; Moreira, João Mendes
Source: Lecture Notes in Computer Science. Conference titles: International Conference on Intelligent Data Engineering and Automated Learning - IDEAL. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, ANÁLISE ESTATÍSTICA DE DADOS, MINERAÇÃO DE DADOS
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ABNT
GARCIA, Kemilly Dearo e CARVALHO, André Carlos Ponce de Leon Ferreira de e MOREIRA, João Mendes. A cluster-based prototype reduction for online classification. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-03493-1_63. Acesso em: 16 nov. 2024. , 2018
APA
Garcia, K. D., Carvalho, A. C. P. de L. F. de, & Moreira, J. M. (2018). A cluster-based prototype reduction for online classification. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-030-03493-1_63
NLM
Garcia KD, Carvalho ACP de LF de, Moreira JM. A cluster-based prototype reduction for online classification [Internet]. Lecture Notes in Computer Science. 2018 ; 11314 603-610.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-03493-1_63
Vancouver
Garcia KD, Carvalho ACP de LF de, Moreira JM. A cluster-based prototype reduction for online classification [Internet]. Lecture Notes in Computer Science. 2018 ; 11314 603-610.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-030-03493-1_63
Trabalho de evento-anais periodico
An accurate flood forecasting model using wireless sensor networks and chaos theory: a case study with real WSN deployment in Brazil (2014)
Furquim, Gustavo; Mello, Rodrigo Fernandes de; Pessin, Gustavo; Faiçal, Bruno S; Mendiondo, Eduardo Mario; Ueyama, Jó
Source: Communications in Computer and Information Science. Conference titles: International Conference on Engineering Applications of Neural Networks - EANN. Unidades: ICMC, EESC
Subjects: SISTEMAS EMBUTIDOS, PROGRAMAÇÃO CONCORRENTE, APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS, TEORIA DO CAOS
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ABNT
FURQUIM, Gustavo et al. An accurate flood forecasting model using wireless sensor networks and chaos theory: a case study with real WSN deployment in Brazil. Communications in Computer and Information Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-11071-4_9. Acesso em: 16 nov. 2024. , 2014
APA
Furquim, G., Mello, R. F. de, Pessin, G., Faiçal, B. S., Mendiondo, E. M., & Ueyama, J. (2014). An accurate flood forecasting model using wireless sensor networks and chaos theory: a case study with real WSN deployment in Brazil. Communications in Computer and Information Science. Cham: Springer. doi:10.1007/978-3-319-11071-4_9
NLM
Furquim G, Mello RF de, Pessin G, Faiçal BS, Mendiondo EM, Ueyama J. An accurate flood forecasting model using wireless sensor networks and chaos theory: a case study with real WSN deployment in Brazil [Internet]. Communications in Computer and Information Science. 2014 ; 459 92-102.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-319-11071-4_9
Vancouver
Furquim G, Mello RF de, Pessin G, Faiçal BS, Mendiondo EM, Ueyama J. An accurate flood forecasting model using wireless sensor networks and chaos theory: a case study with real WSN deployment in Brazil [Internet]. Communications in Computer and Information Science. 2014 ; 459 92-102.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1007/978-3-319-11071-4_9

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