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Artigo de periodico
Big data/analytics platform for Industry 4.0 implementation in advanced manufacturing context (2021)
Bonnard, Renan ; Arantes, Márcio da Silva ; Lorbieski, Rodolfo ; Vieira, Kléber Magno Maciel; Nunes, Marcelo Canzian
Source: International Journal of Advanced Manufacturing Technology. Unidade: ICMC
Subjects: INDÚSTRIA 4.0, BIG DATA, COMPUTAÇÃO EM NUVEM, INTELIGÊNCIA ARTIFICIAL
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ABNT
BONNARD, Renan et al. Big data/analytics platform for Industry 4.0 implementation in advanced manufacturing context. International Journal of Advanced Manufacturing Technology, v. No 2021, n. 5-6, p. 1959-1973, 2021Tradução . . Disponível em: https://doi.org/10.1007/s00170-021-07834-5. Acesso em: 16 ago. 2024.
APA
Bonnard, R., Arantes, M. da S., Lorbieski, R., Vieira, K. M. M., & Nunes, M. C. (2021). Big data/analytics platform for Industry 4.0 implementation in advanced manufacturing context. International Journal of Advanced Manufacturing Technology, No 2021( 5-6), 1959-1973. doi:10.1007/s00170-021-07834-5
NLM
Bonnard R, Arantes M da S, Lorbieski R, Vieira KMM, Nunes MC. Big data/analytics platform for Industry 4.0 implementation in advanced manufacturing context [Internet]. International Journal of Advanced Manufacturing Technology. 2021 ; No 2021( 5-6): 1959-1973.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1007/s00170-021-07834-5
Vancouver
Bonnard R, Arantes M da S, Lorbieski R, Vieira KMM, Nunes MC. Big data/analytics platform for Industry 4.0 implementation in advanced manufacturing context [Internet]. International Journal of Advanced Manufacturing Technology. 2021 ; No 2021( 5-6): 1959-1973.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1007/s00170-021-07834-5
Artigo de periodico
Country transition index based on hierarchical clustering to predict next COVID-19 waves (2021)
Rios, Ricardo Araújo ; Nogueira, Tatiane ; Coimbra, Danilo Barbosa; Lopes, Tiago José da Silva ; Abraham, Ajith ; Mello, Rodrigo Fernandes de
Source: Scientific Reports. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, INTELIGÊNCIA ARTIFICIAL, SURTOS DE DOENÇAS, COVID-19
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ABNT
RIOS, Ricardo Araújo et al. Country transition index based on hierarchical clustering to predict next COVID-19 waves. Scientific Reports, v. 11, p. 1-13, 2021Tradução . . Disponível em: https://doi.org/10.1038/s41598-021-94661-z. Acesso em: 16 ago. 2024.
APA
Rios, R. A., Nogueira, T., Coimbra, D. B., Lopes, T. J. da S., Abraham, A., & Mello, R. F. de. (2021). Country transition index based on hierarchical clustering to predict next COVID-19 waves. Scientific Reports, 11, 1-13. doi:10.1038/s41598-021-94661-z
NLM
Rios RA, Nogueira T, Coimbra DB, Lopes TJ da S, Abraham A, Mello RF de. Country transition index based on hierarchical clustering to predict next COVID-19 waves [Internet]. Scientific Reports. 2021 ; 11 1-13.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1038/s41598-021-94661-z
Vancouver
Rios RA, Nogueira T, Coimbra DB, Lopes TJ da S, Abraham A, Mello RF de. Country transition index based on hierarchical clustering to predict next COVID-19 waves [Internet]. Scientific Reports. 2021 ; 11 1-13.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1038/s41598-021-94661-z
Artigo de periodico-carta/editorial
Special issue HAIS 2014 [Editorial]: recent advancements in hybrid artificial intelligence systems and its application to real-world problems (2019)
Polycarpou, Marios; Carvalho, André Carlos Ponce de Leon Ferreira de ; Pan, Jeng-Shyang; Wozniak, Michal; Quintián, Héctor; Corchado, Emilio
Source: Neurocomputing. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
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ABNT
POLYCARPOU, Marios et al. Special issue HAIS 2014 [Editorial]: recent advancements in hybrid artificial intelligence systems and its application to real-world problems. Neurocomputing. Amsterdam: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. Disponível em: https://doi.org/10.1016/j.neucom.2017.09.001. Acesso em: 16 ago. 2024. , 2019
APA
Polycarpou, M., Carvalho, A. C. P. de L. F. de, Pan, J. -S., Wozniak, M., Quintián, H., & Corchado, E. (2019). Special issue HAIS 2014 [Editorial]: recent advancements in hybrid artificial intelligence systems and its application to real-world problems. Neurocomputing. Amsterdam: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. doi:10.1016/j.neucom.2017.09.001
NLM
Polycarpou M, Carvalho ACP de LF de, Pan J-S, Wozniak M, Quintián H, Corchado E. Special issue HAIS 2014 [Editorial]: recent advancements in hybrid artificial intelligence systems and its application to real-world problems [Internet]. Neurocomputing. 2019 ; 326-327( Ja 2019): 1-2.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.neucom.2017.09.001
Vancouver
Polycarpou M, Carvalho ACP de LF de, Pan J-S, Wozniak M, Quintián H, Corchado E. Special issue HAIS 2014 [Editorial]: recent advancements in hybrid artificial intelligence systems and its application to real-world problems [Internet]. Neurocomputing. 2019 ; 326-327( Ja 2019): 1-2.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.neucom.2017.09.001
Artigo de periodico
Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs (2017)
Faleiros, Thiago de Paulo; Rossi, Rafael Geraldeli; Lopes, Alneu de Andrade
Source: Pattern Recognition Letters. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS
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ABNT
FALEIROS, Thiago de Paulo e ROSSI, Rafael Geraldeli e LOPES, Alneu de Andrade. Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs. Pattern Recognition Letters, v. 87, p. 127-138, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.patrec.2016.04.006. Acesso em: 16 ago. 2024.
APA
Faleiros, T. de P., Rossi, R. G., & Lopes, A. de A. (2017). Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs. Pattern Recognition Letters, 87, 127-138. doi:10.1016/j.patrec.2016.04.006
NLM
Faleiros T de P, Rossi RG, Lopes A de A. Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs [Internet]. Pattern Recognition Letters. 2017 ; 87 127-138.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.patrec.2016.04.006
Vancouver
Faleiros T de P, Rossi RG, Lopes A de A. Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs [Internet]. Pattern Recognition Letters. 2017 ; 87 127-138.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.patrec.2016.04.006
Artigo de periodico
RGCLI: robust graph that considers labeled instances for semi-supervised learning (2017)
Berton, Lilian; Faleiros, Thiago de Paulo; Valejo, Alan; Valverde-Rebaza, Jorge; Lopes, Alneu de Andrade
Source: Neurocomputing. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
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ABNT
BERTON, Lilian et al. RGCLI: robust graph that considers labeled instances for semi-supervised learning. Neurocomputing, v. 226, p. 238-248, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2016.11.053. Acesso em: 16 ago. 2024.
APA
Berton, L., Faleiros, T. de P., Valejo, A., Valverde-Rebaza, J., & Lopes, A. de A. (2017). RGCLI: robust graph that considers labeled instances for semi-supervised learning. Neurocomputing, 226, 238-248. doi:10.1016/j.neucom.2016.11.053
NLM
Berton L, Faleiros T de P, Valejo A, Valverde-Rebaza J, Lopes A de A. RGCLI: robust graph that considers labeled instances for semi-supervised learning [Internet]. Neurocomputing. 2017 ; 226 238-248.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.neucom.2016.11.053
Vancouver
Berton L, Faleiros T de P, Valejo A, Valverde-Rebaza J, Lopes A de A. RGCLI: robust graph that considers labeled instances for semi-supervised learning [Internet]. Neurocomputing. 2017 ; 226 238-248.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.neucom.2016.11.053
Artigo de periodico
A systematic comparative evaluation of biclustering techniques (2017)
Padilha, Victor A; Campello, Ricardo José Gabrielli Barreto
Source: BMC Bioinformatics. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, RECONHECIMENTO DE PADRÕES, BIOINFORMÁTICA, EXPRESSÃO GÊNICA
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ABNT
PADILHA, Victor A e CAMPELLO, Ricardo José Gabrielli Barreto. A systematic comparative evaluation of biclustering techniques. BMC Bioinformatics, v. 18, p. 1-25, 2017Tradução . . Disponível em: https://doi.org/10.1186/s12859-017-1487-1. Acesso em: 16 ago. 2024.
APA
Padilha, V. A., & Campello, R. J. G. B. (2017). A systematic comparative evaluation of biclustering techniques. BMC Bioinformatics, 18, 1-25. doi:10.1186/s12859-017-1487-1
NLM
Padilha VA, Campello RJGB. A systematic comparative evaluation of biclustering techniques [Internet]. BMC Bioinformatics. 2017 ; 18 1-25.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1186/s12859-017-1487-1
Vancouver
Padilha VA, Campello RJGB. A systematic comparative evaluation of biclustering techniques [Internet]. BMC Bioinformatics. 2017 ; 18 1-25.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1186/s12859-017-1487-1
Artigo de periodico
Opinion summarization methods: comparing and extending extractive and abstractive approaches (2017)
Condori, Roque Enrique López; Pardo, Thiago Alexandre Salgueiro
Source: Expert Systems with Applications. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, PROCESSAMENTO DE LINGUAGEM NATURAL, RESUMOS
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ABNT
CONDORI, Roque Enrique López e PARDO, Thiago Alexandre Salgueiro. Opinion summarization methods: comparing and extending extractive and abstractive approaches. Expert Systems with Applications, v. 78, p. 124-134, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2017.02.006. Acesso em: 16 ago. 2024.
APA
Condori, R. E. L., & Pardo, T. A. S. (2017). Opinion summarization methods: comparing and extending extractive and abstractive approaches. Expert Systems with Applications, 78, 124-134. doi:10.1016/j.eswa.2017.02.006
NLM
Condori REL, Pardo TAS. Opinion summarization methods: comparing and extending extractive and abstractive approaches [Internet]. Expert Systems with Applications. 2017 ; 78 124-134.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.eswa.2017.02.006
Vancouver
Condori REL, Pardo TAS. Opinion summarization methods: comparing and extending extractive and abstractive approaches [Internet]. Expert Systems with Applications. 2017 ; 78 124-134.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.eswa.2017.02.006
Artigo de periodico
Improving k-means through distributed scalable metaheuristics (2017)
Oliveira, G. V; Coutinho, F. P; Campello, Ricardo José Gabrielli Barreto; Naldi, M. C
Source: Neurocomputing. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, ALGORITMOS, MINERAÇÃO DE DADOS, HEURÍSTICA, ALGORITMOS GENÉTICOS
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ABNT
OLIVEIRA, G. V et al. Improving k-means through distributed scalable metaheuristics. Neurocomputing, v. 246, p. 45-57, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2016.07.074. Acesso em: 16 ago. 2024.
APA
Oliveira, G. V., Coutinho, F. P., Campello, R. J. G. B., & Naldi, M. C. (2017). Improving k-means through distributed scalable metaheuristics. Neurocomputing, 246, 45-57. doi:10.1016/j.neucom.2016.07.074
NLM
Oliveira GV, Coutinho FP, Campello RJGB, Naldi MC. Improving k-means through distributed scalable metaheuristics [Internet]. Neurocomputing. 2017 ; 246 45-57.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.neucom.2016.07.074
Vancouver
Oliveira GV, Coutinho FP, Campello RJGB, Naldi MC. Improving k-means through distributed scalable metaheuristics [Internet]. Neurocomputing. 2017 ; 246 45-57.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.neucom.2016.07.074
Artigo de periodico
An evolutionary algorithm for clustering data streams with a variable number of clusters (2017)
Silva, Jonathan de Andrade; Hruschka, Eduardo Raul ; Gama, João
Source: Expert Systems with Applications. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, ALGORITMOS GENÉTICOS
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ABNT
SILVA, Jonathan de Andrade e HRUSCHKA, Eduardo Raul e GAMA, João. An evolutionary algorithm for clustering data streams with a variable number of clusters. Expert Systems with Applications, v. 67, n. Ja 2017, p. 228-238, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2016.09.020. Acesso em: 16 ago. 2024.
APA
Silva, J. de A., Hruschka, E. R., & Gama, J. (2017). An evolutionary algorithm for clustering data streams with a variable number of clusters. Expert Systems with Applications, 67( Ja 2017), 228-238. doi:10.1016/j.eswa.2016.09.020
NLM
Silva J de A, Hruschka ER, Gama J. An evolutionary algorithm for clustering data streams with a variable number of clusters [Internet]. Expert Systems with Applications. 2017 ; 67( Ja 2017): 228-238.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.eswa.2016.09.020
Vancouver
Silva J de A, Hruschka ER, Gama J. An evolutionary algorithm for clustering data streams with a variable number of clusters [Internet]. Expert Systems with Applications. 2017 ; 67( Ja 2017): 228-238.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.eswa.2016.09.020
Artigo de periodico
Intelligent-guided adaptive search for the maximum covering location problem (2017)
Máximo, Vinícius R; Nascimento, Mariá C. V; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Computers and Operations Research. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, HEURÍSTICA
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ABNT
MÁXIMO, Vinícius R e NASCIMENTO, Mariá C. V e CARVALHO, André Carlos Ponce de Leon Ferreira de. Intelligent-guided adaptive search for the maximum covering location problem. Computers and Operations Research, v. 78, p. 129-137, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.cor.2016.08.018. Acesso em: 16 ago. 2024.
APA
Máximo, V. R., Nascimento, M. C. V., & Carvalho, A. C. P. de L. F. de. (2017). Intelligent-guided adaptive search for the maximum covering location problem. Computers and Operations Research, 78, 129-137. doi:10.1016/j.cor.2016.08.018
NLM
Máximo VR, Nascimento MCV, Carvalho ACP de LF de. Intelligent-guided adaptive search for the maximum covering location problem [Internet]. Computers and Operations Research. 2017 ; 78 129-137.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.cor.2016.08.018
Vancouver
Máximo VR, Nascimento MCV, Carvalho ACP de LF de. Intelligent-guided adaptive search for the maximum covering location problem [Internet]. Computers and Operations Research. 2017 ; 78 129-137.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.cor.2016.08.018
Artigo de periodico
How an epileptic EEG segment, used as reference, can influence a cross-correlation classifier? (2017)
Oliva, Jefferson Tales; Rosa, João Luís Garcia
Source: Applied Intelligence. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE SINAIS, MINERAÇÃO DE DADOS, ELETROENCEFALOGRAFIA, EPILEPSIA
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ABNT
OLIVA, Jefferson Tales e ROSA, João Luís Garcia. How an epileptic EEG segment, used as reference, can influence a cross-correlation classifier?. Applied Intelligence, v. 47, n. 1, p. 178-196, 2017Tradução . . Disponível em: https://doi.org/10.1007/s10489-016-0891-y. Acesso em: 16 ago. 2024.
APA
Oliva, J. T., & Rosa, J. L. G. (2017). How an epileptic EEG segment, used as reference, can influence a cross-correlation classifier? Applied Intelligence, 47( 1), 178-196. doi:10.1007/s10489-016-0891-y
NLM
Oliva JT, Rosa JLG. How an epileptic EEG segment, used as reference, can influence a cross-correlation classifier? [Internet]. Applied Intelligence. 2017 ; 47( 1): 178-196.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1007/s10489-016-0891-y
Vancouver
Oliva JT, Rosa JLG. How an epileptic EEG segment, used as reference, can influence a cross-correlation classifier? [Internet]. Applied Intelligence. 2017 ; 47( 1): 178-196.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1007/s10489-016-0891-y
Artigo de periodico
Evolutionary computing in recommender systems: a review of recent research (2017)
Horváth, Tomás; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Natural Computing. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, COMPUTAÇÃO EVOLUTIVA, ALGORITMOS GENÉTICOS
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ABNT
HORVÁTH, Tomás e CARVALHO, André Carlos Ponce de Leon Ferreira de. Evolutionary computing in recommender systems: a review of recent research. Natural Computing, v. 16, n. 3, p. Se 2017, 2017Tradução . . Disponível em: https://doi.org/10.1007/s11047-016-9540-y. Acesso em: 16 ago. 2024.
APA
Horváth, T., & Carvalho, A. C. P. de L. F. de. (2017). Evolutionary computing in recommender systems: a review of recent research. Natural Computing, 16( 3), Se 2017. doi:10.1007/s11047-016-9540-y
NLM
Horváth T, Carvalho ACP de LF de. Evolutionary computing in recommender systems: a review of recent research [Internet]. Natural Computing. 2017 ; 16( 3): Se 2017.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1007/s11047-016-9540-y
Vancouver
Horváth T, Carvalho ACP de LF de. Evolutionary computing in recommender systems: a review of recent research [Internet]. Natural Computing. 2017 ; 16( 3): Se 2017.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1007/s11047-016-9540-y
Artigo de periodico
A support system for clustering data streams with a variable number of clusters (2016)
Silva, Jonathan de Andrade; Hruschka, Eduardo Raul
Source: ACM Transactions on Autonomous and Adaptive Systems. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, RECONHECIMENTO DE PADRÕES, ALGORITMOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Jonathan de Andrade e HRUSCHKA, Eduardo Raul. A support system for clustering data streams with a variable number of clusters. ACM Transactions on Autonomous and Adaptive Systems, v. 11, n. 2, p. 11:1-11:26, 2016Tradução . . Disponível em: https://doi.org/10.1145/2932704. Acesso em: 16 ago. 2024.
APA
Silva, J. de A., & Hruschka, E. R. (2016). A support system for clustering data streams with a variable number of clusters. ACM Transactions on Autonomous and Adaptive Systems, 11( 2), 11:1-11:26. doi:10.1145/2932704
NLM
Silva J de A, Hruschka ER. A support system for clustering data streams with a variable number of clusters [Internet]. ACM Transactions on Autonomous and Adaptive Systems. 2016 ; 11( 2): 11:1-11:26.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1145/2932704
Vancouver
Silva J de A, Hruschka ER. A support system for clustering data streams with a variable number of clusters [Internet]. ACM Transactions on Autonomous and Adaptive Systems. 2016 ; 11( 2): 11:1-11:26.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1145/2932704
Artigo de periodico
Novelty detection in data stream (2016)
Faria, Elaine R; Gonçalves, Isabel J. C. R; Carvalho, André Carlos Ponce de Leon Ferreira de ; Gama, João
Source: Artificial Intelligence Review. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, RECONHECIMENTO DE PADRÕES
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ABNT
FARIA, Elaine R et al. Novelty detection in data stream. Artificial Intelligence Review, v. 45, n. 2, p. 235-269, 2016Tradução . . Disponível em: https://doi.org/10.1007/s10462-015-9444-8. Acesso em: 16 ago. 2024.
APA
Faria, E. R., Gonçalves, I. J. C. R., Carvalho, A. C. P. de L. F. de, & Gama, J. (2016). Novelty detection in data stream. Artificial Intelligence Review, 45( 2), 235-269. doi:10.1007/s10462-015-9444-8
NLM
Faria ER, Gonçalves IJCR, Carvalho ACP de LF de, Gama J. Novelty detection in data stream [Internet]. Artificial Intelligence Review. 2016 ; 45( 2): 235-269.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1007/s10462-015-9444-8
Vancouver
Faria ER, Gonçalves IJCR, Carvalho ACP de LF de, Gama J. Novelty detection in data stream [Internet]. Artificial Intelligence Review. 2016 ; 45( 2): 235-269.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1007/s10462-015-9444-8
Artigo de periodico
Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem: a comparison of meta-features (2016)
Kanda, Jorge; Carvalho, André Carlos Ponce de Leon Ferreira de ; Hruschka, Eduardo Raul ; Soares, Carlos; Brazdil, Pavel
Source: Neurocomputing. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, HEURÍSTICA
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ABNT
KANDA, Jorge et al. Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem: a comparison of meta-features. Neurocomputing, v. 205, p. Se 2016, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2016.04.027. Acesso em: 16 ago. 2024.
APA
Kanda, J., Carvalho, A. C. P. de L. F. de, Hruschka, E. R., Soares, C., & Brazdil, P. (2016). Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem: a comparison of meta-features. Neurocomputing, 205, Se 2016. doi:10.1016/j.neucom.2016.04.027
NLM
Kanda J, Carvalho ACP de LF de, Hruschka ER, Soares C, Brazdil P. Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem: a comparison of meta-features [Internet]. Neurocomputing. 2016 ; 205 Se 2016.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.neucom.2016.04.027
Vancouver
Kanda J, Carvalho ACP de LF de, Hruschka ER, Soares C, Brazdil P. Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem: a comparison of meta-features [Internet]. Neurocomputing. 2016 ; 205 Se 2016.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.neucom.2016.04.027
Artigo de periodico
Noise detection in the meta-learning level (2016)
Garcia, Luís P. F; Carvalho, André Carlos Ponce de Leon Ferreira de ; Lorena, Ana C
Source: Neurocomputing. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
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ABNT
GARCIA, Luís P. F e CARVALHO, André Carlos Ponce de Leon Ferreira de e LORENA, Ana C. Noise detection in the meta-learning level. Neurocomputing, v. 176, p. 14-25, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2014.12.100. Acesso em: 16 ago. 2024.
APA
Garcia, L. P. F., Carvalho, A. C. P. de L. F. de, & Lorena, A. C. (2016). Noise detection in the meta-learning level. Neurocomputing, 176, 14-25. doi:10.1016/j.neucom.2014.12.100
NLM
Garcia LPF, Carvalho ACP de LF de, Lorena AC. Noise detection in the meta-learning level [Internet]. Neurocomputing. 2016 ; 176 14-25.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.neucom.2014.12.100
Vancouver
Garcia LPF, Carvalho ACP de LF de, Lorena AC. Noise detection in the meta-learning level [Internet]. Neurocomputing. 2016 ; 176 14-25.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.neucom.2014.12.100
Artigo de periodico
Image quantization as a dimensionality reduction procedure in color and texture feature extraction (2016)
Ponti, Moacir Antonelli ; Nazaré, Tiago Santana de ; Thumé, Gabriela S
Source: Neurocomputing. Unidade: ICMC
Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PONTI, Moacir Antonelli e NAZARÉ, Tiago Santana de e THUMÉ, Gabriela S. Image quantization as a dimensionality reduction procedure in color and texture feature extraction. Neurocomputing, v. 173, n. Ja 2016, p. 385-396, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2015.04.114. Acesso em: 16 ago. 2024.
APA
Ponti, M. A., Nazaré, T. S. de, & Thumé, G. S. (2016). Image quantization as a dimensionality reduction procedure in color and texture feature extraction. Neurocomputing, 173( Ja 2016), 385-396. doi:10.1016/j.neucom.2015.04.114
NLM
Ponti MA, Nazaré TS de, Thumé GS. Image quantization as a dimensionality reduction procedure in color and texture feature extraction [Internet]. Neurocomputing. 2016 ; 173( Ja 2016): 385-396.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.neucom.2015.04.114
Vancouver
Ponti MA, Nazaré TS de, Thumé GS. Image quantization as a dimensionality reduction procedure in color and texture feature extraction [Internet]. Neurocomputing. 2016 ; 173( Ja 2016): 385-396.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.neucom.2015.04.114
Artigo de periodico
Genetic generation of fuzzy systems with rule extraction using formal concept analysis (2016)
Cintra, M. E; Camargo, H. A; Monard, Maria Carolina
Source: Information Sciences. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, FUZZY (INTELIGÊNCIA ARTIFICIAL)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CINTRA, M. E e CAMARGO, H. A e MONARD, Maria Carolina. Genetic generation of fuzzy systems with rule extraction using formal concept analysis. Information Sciences, v. 349-350, p. 199-215, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2016.02.026. Acesso em: 16 ago. 2024.
APA
Cintra, M. E., Camargo, H. A., & Monard, M. C. (2016). Genetic generation of fuzzy systems with rule extraction using formal concept analysis. Information Sciences, 349-350, 199-215. doi:10.1016/j.ins.2016.02.026
NLM
Cintra ME, Camargo HA, Monard MC. Genetic generation of fuzzy systems with rule extraction using formal concept analysis [Internet]. Information Sciences. 2016 ; 349-350 199-215.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.ins.2016.02.026
Vancouver
Cintra ME, Camargo HA, Monard MC. Genetic generation of fuzzy systems with rule extraction using formal concept analysis [Internet]. Information Sciences. 2016 ; 349-350 199-215.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1016/j.ins.2016.02.026
Artigo de periodico
On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study (2016)
Campos, Guilherme O; Zimek, Arthur; Sander, Jörg; Campello, Ricardo José Gabrielli Barreto; Micenková, Barbora; Schubert, Erich; Assent, Ira; Houle, Michael E
Source: Data Mining and Knowledge Discovery. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAMPOS, Guilherme O et al. On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study. Data Mining and Knowledge Discovery, v. 30, n. 4, p. 891-927, 2016Tradução . . Disponível em: https://doi.org/10.1007/s10618-015-0444-8. Acesso em: 16 ago. 2024.
APA
Campos, G. O., Zimek, A., Sander, J., Campello, R. J. G. B., Micenková, B., Schubert, E., et al. (2016). On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study. Data Mining and Knowledge Discovery, 30( 4), 891-927. doi:10.1007/s10618-015-0444-8
NLM
Campos GO, Zimek A, Sander J, Campello RJGB, Micenková B, Schubert E, Assent I, Houle ME. On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study [Internet]. Data Mining and Knowledge Discovery. 2016 ; 30( 4): 891-927.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1007/s10618-015-0444-8
Vancouver
Campos GO, Zimek A, Sander J, Campello RJGB, Micenková B, Schubert E, Assent I, Houle ME. On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study [Internet]. Data Mining and Knowledge Discovery. 2016 ; 30( 4): 891-927.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1007/s10618-015-0444-8
Artigo de periodico
MINAS: multiclass learning algorithm for novelty detection in data streams (2016)
Faria, Elaine Ribeiro de; Carvalho, André Carlos Ponce de Leon Ferreira de ; Gama, João
Source: Data Mining and Knowledge Discovery. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FARIA, Elaine Ribeiro de e CARVALHO, André Carlos Ponce de Leon Ferreira de e GAMA, João. MINAS: multiclass learning algorithm for novelty detection in data streams. Data Mining and Knowledge Discovery, v. 30, n. 3, p. 640-680, 2016Tradução . . Disponível em: https://doi.org/10.1007/s10618-015-0433-y. Acesso em: 16 ago. 2024.
APA
Faria, E. R. de, Carvalho, A. C. P. de L. F. de, & Gama, J. (2016). MINAS: multiclass learning algorithm for novelty detection in data streams. Data Mining and Knowledge Discovery, 30( 3), 640-680. doi:10.1007/s10618-015-0433-y
NLM
Faria ER de, Carvalho ACP de LF de, Gama J. MINAS: multiclass learning algorithm for novelty detection in data streams [Internet]. Data Mining and Knowledge Discovery. 2016 ; 30( 3): 640-680.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1007/s10618-015-0433-y
Vancouver
Faria ER de, Carvalho ACP de LF de, Gama J. MINAS: multiclass learning algorithm for novelty detection in data streams [Internet]. Data Mining and Knowledge Discovery. 2016 ; 30( 3): 640-680.[citado 2024 ago. 16 ] Available from: https://doi.org/10.1007/s10618-015-0433-y

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