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Filtros : "Liang, Zhao" Limpar

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  • Artigo de periodico

    Stock market trend detection and automatic decision-making through a network-based classification model (2021)

    Colliri, Tiago Santos ; Liang, Zhao

    Source: Natural Computing. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, BOLSA DE VALORES

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      COLLIRI, Tiago Santos; LIANG, Zhao. Stock market trend detection and automatic decision-making through a network-based classification model. Natural Computing, Dordrecht, 2021. Disponível em: < https://doi.org/10.1007/s11047-020-09829-9 > DOI: 10.1007/s11047-020-09829-9.

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      Colliri, T. S., & Liang, Z. (2021). Stock market trend detection and automatic decision-making through a network-based classification model. Natural Computing. doi:10.1007/s11047-020-09829-9

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      Colliri TS, Liang Z. Stock market trend detection and automatic decision-making through a network-based classification model [Internet]. Natural Computing. 2021 ;Available from: https://doi.org/10.1007/s11047-020-09829-9

    • Vancouver

      Colliri TS, Liang Z. Stock market trend detection and automatic decision-making through a network-based classification model [Internet]. Natural Computing. 2021 ;Available from: https://doi.org/10.1007/s11047-020-09829-9

  • Tese

    Clustered Echo State networks for signal denoising and frequency filtering (2020)

    Oliveira Junior, Laercio de; Liang, Zhao (Orientador)

    Unidade: FFCLRP

    Subjects: REDES COMPLEXAS, REDES NEURAIS, COMPUTAÇÃO APLICADA, ANÁLISE DE SÉRIES TEMPORAIS

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      OLIVEIRA JUNIOR, Laercio de; LIANG, Zhao. Clustered Echo State networks for signal denoising and frequency filtering. 2020.Universidade de São Paulo, Ribeirão Preto, 2020. Disponível em: < https://www.teses.usp.br/teses/disponiveis/59/59143/tde-28022021-205755/ >.

    • APA

      Oliveira Junior, L. de, & Liang, Z. (2020). Clustered Echo State networks for signal denoising and frequency filtering. Universidade de São Paulo, Ribeirão Preto. Recuperado de https://www.teses.usp.br/teses/disponiveis/59/59143/tde-28022021-205755/

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      Oliveira Junior L de, Liang Z. Clustered Echo State networks for signal denoising and frequency filtering [Internet]. 2020 ;Available from: https://www.teses.usp.br/teses/disponiveis/59/59143/tde-28022021-205755/

    • Vancouver

      Oliveira Junior L de, Liang Z. Clustered Echo State networks for signal denoising and frequency filtering [Internet]. 2020 ;Available from: https://www.teses.usp.br/teses/disponiveis/59/59143/tde-28022021-205755/

  • Trabalho de evento

    An optimized modularity-based high level classification model (2020)

    Colliri, Tiago Santos ; Weiguang, Liu; Liang, Zhao

    Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, RECONHECIMENTO DE PADRÕES

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      COLLIRI, Tiago Santos; WEIGUANG, Liu; LIANG, Zhao. An optimized modularity-based high level classification model. Anais.. Piscataway: IEEE, 2020.Disponível em: DOI: 10.1109/IJCNN48605.2020.9206755.

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      Colliri, T. S., Weiguang, L., & Liang, Z. (2020). An optimized modularity-based high level classification model. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN48605.2020.9206755

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      Colliri TS, Weiguang L, Liang Z. An optimized modularity-based high level classification model [Internet]. Proceedings. 2020 ;Available from: https://doi.org/10.1109/IJCNN48605.2020.9206755

    • Vancouver

      Colliri TS, Weiguang L, Liang Z. An optimized modularity-based high level classification model [Internet]. Proceedings. 2020 ;Available from: https://doi.org/10.1109/IJCNN48605.2020.9206755

  • Artigo de periodico

    A tourist walk approach for internal and external outlier detection (2020)

    Rodrigues, Rafael Delalibera ; Liang, Zhao ; Zheng, Qiusheng; Zhang, Junbao

    Source: Neurocomputing. Unidades: FFCLRP, ICMC

    Subjects: TURISMO, MEMÓRIA (ELETRÔNICA DIGITAL), ATRATORES

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      RODRIGUES, Rafael Delalibera; LIANG, Zhao; ZHENG, Qiusheng; ZHANG, Junbao. A tourist walk approach for internal and external outlier detection. Neurocomputing, Amsterdam, v. 393, p. 203-213, 2020. Disponível em: < https://doi.org/10.1016/j.neucom.2018.10.113 > DOI: 10.1016/j.neucom.2018.10.113.

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      Rodrigues, R. D., Liang, Z., Zheng, Q., & Zhang, J. (2020). A tourist walk approach for internal and external outlier detection. Neurocomputing, 393, 203-213. doi:10.1016/j.neucom.2018.10.113

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      Rodrigues RD, Liang Z, Zheng Q, Zhang J. A tourist walk approach for internal and external outlier detection [Internet]. Neurocomputing. 2020 ; 393 203-213.Available from: https://doi.org/10.1016/j.neucom.2018.10.113

    • Vancouver

      Rodrigues RD, Liang Z, Zheng Q, Zhang J. A tourist walk approach for internal and external outlier detection [Internet]. Neurocomputing. 2020 ; 393 203-213.Available from: https://doi.org/10.1016/j.neucom.2018.10.113

  • Trabalho de evento-anais periodico

    Particle competition for unbalanced community detection in complex networks (2020)

    Martins, Luan Vinicius Carvalho; Liang, Zhao

    Source: Lecture Notes in Artificial Intelligence. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: FFCLRP, ICMC

    Assunto: REDES COMPLEXAS

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      MARTINS, Luan Vinicius Carvalho; LIANG, Zhao. Particle competition for unbalanced community detection in complex networks. Lecture Notes in Artificial Intelligence[S.l: s.n.], 2020.Disponível em: DOI: 10.1007/978-3-030-61380-8_22.

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      Martins, L. V. C., & Liang, Z. (2020). Particle competition for unbalanced community detection in complex networks. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-61380-8_22

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      Martins LVC, Liang Z. Particle competition for unbalanced community detection in complex networks [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 322-336.Available from: https://doi.org/10.1007/978-3-030-61380-8_22

    • Vancouver

      Martins LVC, Liang Z. Particle competition for unbalanced community detection in complex networks [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 322-336.Available from: https://doi.org/10.1007/978-3-030-61380-8_22

  • Artigo de periodico

    Temporal network pattern identification by community modelling (2020)

    Gao, Xubo; Zheng, Qiusheng; Vega-Oliveros, Didier Augusto ; Anghinoni, Leandro ; Liang, Zhao

    Source: Scientific Reports. Unidades: FFCLRP, ICMC

    Subjects: MINERAÇÃO DE DADOS, ANÁLISE DE SÉRIES TEMPORAIS, RECONHECIMENTO DE PADRÕES

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      GAO, Xubo; ZHENG, Qiusheng; VEGA-OLIVEROS, Didier Augusto; ANGHINONI, Leandro; LIANG, Zhao. Temporal network pattern identification by community modelling. Scientific Reports, London, v. 10, p. 1-12, 2020. Disponível em: < https://doi.org/10.1038/s41598-019-57123-1 > DOI: 10.1038/s41598-019-57123-1.

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      Gao, X., Zheng, Q., Vega-Oliveros, D. A., Anghinoni, L., & Liang, Z. (2020). Temporal network pattern identification by community modelling. Scientific Reports, 10, 1-12. doi:10.1038/s41598-019-57123-1

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      Gao X, Zheng Q, Vega-Oliveros DA, Anghinoni L, Liang Z. Temporal network pattern identification by community modelling [Internet]. Scientific Reports. 2020 ; 10 1-12.Available from: https://doi.org/10.1038/s41598-019-57123-1

    • Vancouver

      Gao X, Zheng Q, Vega-Oliveros DA, Anghinoni L, Liang Z. Temporal network pattern identification by community modelling [Internet]. Scientific Reports. 2020 ; 10 1-12.Available from: https://doi.org/10.1038/s41598-019-57123-1

  • Tese

    Análise de imagens de radiografia de pacientes com COVID-19 utilizando técnica de classificação de alto nível baseada em redes complexas (2020)

    Pereira, Everson José de Freitas; Liang, Zhao (Orientador)

    Unidade: FFCLRP

    Subjects: COVID-19, REDES COMPLEXAS, DIAGNÓSTICO POR IMAGEM, INTELIGÊNCIA ARTIFICIAL, RAIOS X, TÓRAX

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      PEREIRA, Everson José de Freitas; LIANG, Zhao. Análise de imagens de radiografia de pacientes com COVID-19 utilizando técnica de classificação de alto nível baseada em redes complexas. 2020.Universidade de São Paulo, Ribeirão Preto, 2020. Disponível em: < https://www.teses.usp.br/teses/disponiveis/59/59143/tde-18112020-094205/ >.

    • APA

      Pereira, E. J. de F., & Liang, Z. (2020). Análise de imagens de radiografia de pacientes com COVID-19 utilizando técnica de classificação de alto nível baseada em redes complexas. Universidade de São Paulo, Ribeirão Preto. Recuperado de https://www.teses.usp.br/teses/disponiveis/59/59143/tde-18112020-094205/

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      Pereira EJ de F, Liang Z. Análise de imagens de radiografia de pacientes com COVID-19 utilizando técnica de classificação de alto nível baseada em redes complexas [Internet]. 2020 ;Available from: https://www.teses.usp.br/teses/disponiveis/59/59143/tde-18112020-094205/

    • Vancouver

      Pereira EJ de F, Liang Z. Análise de imagens de radiografia de pacientes com COVID-19 utilizando técnica de classificação de alto nível baseada em redes complexas [Internet]. 2020 ;Available from: https://www.teses.usp.br/teses/disponiveis/59/59143/tde-18112020-094205/

  • Trabalho de evento

    Echo state network performance analysis using non-random topologies (2020)

    Arroyo, Diana Carolina Roca ; Florez, Alexander Ylnner Choquenaira ; Flores, Daniela Milón ; Romero, Roseli Aparecida Francelin ; Liang, Zhao

    Source: Proceedings. Conference titles: IEEE Colombian Conference on Applications of Computational Intelligence - ColCACI. Unidades: ICMC, FFCLRP

    Subjects: SISTEMAS DINÂMICOS, ANÁLISE DE SÉRIES TEMPORAIS, REDES COMPLEXAS

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      ARROYO, Diana Carolina Roca; FLOREZ, Alexander Ylnner Choquenaira; FLORES, Daniela Milón; ROMERO, Roseli Aparecida Francelin; LIANG, Zhao. Echo state network performance analysis using non-random topologies. Anais.. Danvers: IEEE, 2020.Disponível em: DOI: 10.1109/ColCACI50549.2020.9248714.

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      Arroyo, D. C. R., Florez, A. Y. C., Flores, D. M., Romero, R. A. F., & Liang, Z. (2020). Echo state network performance analysis using non-random topologies. In Proceedings. Danvers: IEEE. doi:10.1109/ColCACI50549.2020.9248714

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      Arroyo DCR, Florez AYC, Flores DM, Romero RAF, Liang Z. Echo state network performance analysis using non-random topologies [Internet]. Proceedings. 2020 ;Available from: https://doi.org/10.1109/ColCACI50549.2020.9248714

    • Vancouver

      Arroyo DCR, Florez AYC, Flores DM, Romero RAF, Liang Z. Echo state network performance analysis using non-random topologies [Internet]. Proceedings. 2020 ;Available from: https://doi.org/10.1109/ColCACI50549.2020.9248714

  • Curadoria

    Conferência Brasileira de Dinâmica, Controle e Aplicações - DINCON 2019 (2019)

    Liang, Zhao (cur) ; Maia, Leonardo Paulo (cur) ; Varela, Hamilton (cur) ; Costa, Luciano da Fontoura (cur) ; Koberle, Roland (cur) ; Silva, José Reinaldo (cur) ; Proença, Sérgio Persival Baroncini (cur) ; Asada, Eduardo Nobuhiro (cur)

    Unidades: FFCLRP, EP, EESC, IFSC, IQSC

    Subjects: MATEMÁTICA APLICADA, NEUROCIÊNCIAS, FÍSICA COMPUTACIONAL

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      LIANG, Zhao; MAIA, Leonardo Paulo; VARELA, Hamilton; et al. Conferência Brasileira de Dinâmica, Controle e Aplicações - DINCON 2019. [S.l: s.n.], 2019.Disponível em: .

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      Liang, Z., Maia, L. P., Varela, H., Costa, L. da F., Koberle, R., Silva, J. R., et al. (2019). Conferência Brasileira de Dinâmica, Controle e Aplicações - DINCON 2019. São Carlos: Universidade de São Paulo - USP. Recuperado de http://143.107.182.36/dincon2019/index.php/comite-cientifico/

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      Liang Z, Maia LP, Varela H, Costa L da F, Koberle R, Silva JR, Proença SPB, Asada EN. Conferência Brasileira de Dinâmica, Controle e Aplicações - DINCON 2019 [Internet]. 2019 ;Available from: http://143.107.182.36/dincon2019/index.php/comite-cientifico/

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      Liang Z, Maia LP, Varela H, Costa L da F, Koberle R, Silva JR, Proença SPB, Asada EN. Conferência Brasileira de Dinâmica, Controle e Aplicações - DINCON 2019 [Internet]. 2019 ;Available from: http://143.107.182.36/dincon2019/index.php/comite-cientifico/

  • Tese

    Topologia computacional para análise de série temporal (2019)

    Miranda, Vanderlei Luiz Daneluz; Liang, Zhao (Orientador)

    Unidade: FFCLRP

    Subjects: COMPUTAÇÃO APLICADA, ANÁLISE DE SÉRIES TEMPORAIS, DESCOBERTA DE CONHECIMENTO

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      MIRANDA, Vanderlei Luiz Daneluz; LIANG, Zhao. Topologia computacional para análise de série temporal. 2019.Universidade de São Paulo, Ribeirão Preto, 2019. Disponível em: < http://www.teses.usp.br/teses/disponiveis/59/59143/tde-13052019-175021/ >.

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      Miranda, V. L. D., & Liang, Z. (2019). Topologia computacional para análise de série temporal. Universidade de São Paulo, Ribeirão Preto. Recuperado de http://www.teses.usp.br/teses/disponiveis/59/59143/tde-13052019-175021/

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      Miranda VLD, Liang Z. Topologia computacional para análise de série temporal [Internet]. 2019 ;Available from: http://www.teses.usp.br/teses/disponiveis/59/59143/tde-13052019-175021/

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      Miranda VLD, Liang Z. Topologia computacional para análise de série temporal [Internet]. 2019 ;Available from: http://www.teses.usp.br/teses/disponiveis/59/59143/tde-13052019-175021/

  • Artigo de periodico

    Analyzing the Bills-Voting dynamics and predicting corruption-convictions among brazilian congressmen through temporal networks (2019)

    Colliri, Tiago Santos ; Liang, Zhao

    Source: Scientific Reports. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, ANÁLISE DE SÉRIES TEMPORAIS, CONGRESSO NACIONAL, CORRUPÇÃO

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      COLLIRI, Tiago Santos; LIANG, Zhao. Analyzing the Bills-Voting dynamics and predicting corruption-convictions among brazilian congressmen through temporal networks. Scientific Reports, London, v. No 2019, p. 16754-1-16754-11, 2019. Disponível em: < https://doi.org/10.1038/s41598-019-53252-9 > DOI: 10.1038/s41598-019-53252-9.

    • APA

      Colliri, T. S., & Liang, Z. (2019). Analyzing the Bills-Voting dynamics and predicting corruption-convictions among brazilian congressmen through temporal networks. Scientific Reports, No 2019, 16754-1-16754-11. doi:10.1038/s41598-019-53252-9

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      Colliri TS, Liang Z. Analyzing the Bills-Voting dynamics and predicting corruption-convictions among brazilian congressmen through temporal networks [Internet]. Scientific Reports. 2019 ; No 2019 16754-1-16754-11.Available from: https://doi.org/10.1038/s41598-019-53252-9

    • Vancouver

      Colliri TS, Liang Z. Analyzing the Bills-Voting dynamics and predicting corruption-convictions among brazilian congressmen through temporal networks [Internet]. Scientific Reports. 2019 ; No 2019 16754-1-16754-11.Available from: https://doi.org/10.1038/s41598-019-53252-9

  • Artigo de periodico

    Algorithms to compute the burrows-wheeler similarity distribution (2019)

    Louza, Felipe Alves da ; Telles, Guilherme Pimentel ; Gog, Simon; Liang, Zhao

    Source: Theoretical Computer Science. Unidade: FFCLRP

    Subjects: ALGORITMOS, COMPUTABILIDADE E COMPLEXIDADE

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      LOUZA, Felipe Alves da; TELLES, Guilherme Pimentel; GOG, Simon; LIANG, Zhao. Algorithms to compute the burrows-wheeler similarity distribution. Theoretical Computer Science, Amsterdam, v. 782, p. 145-156, 2019. Disponível em: < http://dx.doi.org/10.1016/j.tcs.2019.03.012 > DOI: 10.1016/j.tcs.2019.03.012.

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      Louza, F. A. da, Telles, G. P., Gog, S., & Liang, Z. (2019). Algorithms to compute the burrows-wheeler similarity distribution. Theoretical Computer Science, 782, 145-156. doi:10.1016/j.tcs.2019.03.012

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      Louza FA da, Telles GP, Gog S, Liang Z. Algorithms to compute the burrows-wheeler similarity distribution [Internet]. Theoretical Computer Science. 2019 ; 782 145-156.Available from: http://dx.doi.org/10.1016/j.tcs.2019.03.012

    • Vancouver

      Louza FA da, Telles GP, Gog S, Liang Z. Algorithms to compute the burrows-wheeler similarity distribution [Internet]. Theoretical Computer Science. 2019 ; 782 145-156.Available from: http://dx.doi.org/10.1016/j.tcs.2019.03.012

  • Trabalho de evento

    Particle competition for multilayer network community detection (2019)

    Gao, Xubo; Zheng, Qiusheng; Verri, Filipe Alves Neto ; Rodrigues, Rafael Delalibera ; Liang, Zhao

    Source: Proceedings. Conference titles: International Conference on Machine Learning and Computing - ICMLC. Unidades: FFCLRP, ICMC

    Subjects: TEORIA DA COMPUTAÇÃO, ALGORITMOS, APRENDIZADO COMPUTACIONAL

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      GAO, Xubo; ZHENG, Qiusheng; VERRI, Filipe Alves Neto; RODRIGUES, Rafael Delalibera; LIANG, Zhao. Particle competition for multilayer network community detection. Anais.. New York: ACM, 2019.Disponível em: DOI: 10.1145/3318299.3318320.

    • APA

      Gao, X., Zheng, Q., Verri, F. A. N., Rodrigues, R. D., & Liang, Z. (2019). Particle competition for multilayer network community detection. In Proceedings. New York: ACM. doi:10.1145/3318299.3318320

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      Gao X, Zheng Q, Verri FAN, Rodrigues RD, Liang Z. Particle competition for multilayer network community detection [Internet]. Proceedings. 2019 ;Available from: http://dx.doi.org/10.1145/3318299.3318320

    • Vancouver

      Gao X, Zheng Q, Verri FAN, Rodrigues RD, Liang Z. Particle competition for multilayer network community detection [Internet]. Proceedings. 2019 ;Available from: http://dx.doi.org/10.1145/3318299.3318320

  • Trabalho de evento

    A network-based model for optimizing returns in the stock market (2019)

    Colliri, Tiago Santos ; Liang, Zhao

    Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: FFCLRP, ICMC

    Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, BOLSA DE VALORES

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      COLLIRI, Tiago Santos; LIANG, Zhao. A network-based model for optimizing returns in the stock market. Anais.. Piscataway: IEEE, 2019.Disponível em: DOI: 10.1109/BRACIS.2019.00118.

    • APA

      Colliri, T. S., & Liang, Z. (2019). A network-based model for optimizing returns in the stock market. In Proceedings. Piscataway: IEEE. doi:10.1109/BRACIS.2019.00118

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      Colliri TS, Liang Z. A network-based model for optimizing returns in the stock market [Internet]. Proceedings. 2019 ;Available from: https://doi.org/10.1109/BRACIS.2019.00118

    • Vancouver

      Colliri TS, Liang Z. A network-based model for optimizing returns in the stock market [Internet]. Proceedings. 2019 ;Available from: https://doi.org/10.1109/BRACIS.2019.00118

  • Artigo de periodico

    Organizational data classification based on the importance concept of complex networks (2018)

    Carneiro, Murillo Guimarães; Liang, Zhao

    Source: IEEE Transactions on Neural Networks and Learning Systems. Unidade: FFCLRP

    Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES

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      CARNEIRO, Murillo Guimarães; LIANG, Zhao. Organizational data classification based on the importance concept of complex networks. IEEE Transactions on Neural Networks and Learning Systems, Piscataway, v. 29, n. 8, p. 3361-3373, 2018. Disponível em: < http://dx.doi.org/10.1109/TNNLS.2017.2726082 > DOI: 10.1109/TNNLS.2017.2726082.

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      Carneiro, M. G., & Liang, Z. (2018). Organizational data classification based on the importance concept of complex networks. IEEE Transactions on Neural Networks and Learning Systems, 29( 8), 3361-3373. doi:10.1109/TNNLS.2017.2726082

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      Carneiro MG, Liang Z. Organizational data classification based on the importance concept of complex networks [Internet]. IEEE Transactions on Neural Networks and Learning Systems. 2018 ; 29( 8): 3361-3373.Available from: http://dx.doi.org/10.1109/TNNLS.2017.2726082

    • Vancouver

      Carneiro MG, Liang Z. Organizational data classification based on the importance concept of complex networks [Internet]. IEEE Transactions on Neural Networks and Learning Systems. 2018 ; 29( 8): 3361-3373.Available from: http://dx.doi.org/10.1109/TNNLS.2017.2726082

  • Curadoria

    Brazilian Conference on Intelligent Systems (BRACIS), 7 (2018)

    Liang, Zhao (cur)

    Unidade: FFCLRP

    Subjects: CONFERÊNCIA INTERNACIONAL, CURADORIA

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      LIANG, Zhao. Brazilian Conference on Intelligent Systems (BRACIS), 7. [S.l: s.n.], 2018.Disponível em: .

    • APA

      Liang, Z. (2018). Brazilian Conference on Intelligent Systems (BRACIS), 7. São Paulo: SBC. Recuperado de https://bracis2018.mybluemix.net/

    • NLM

      Liang Z. Brazilian Conference on Intelligent Systems (BRACIS), 7 [Internet]. 2018 ;Available from: https://bracis2018.mybluemix.net/

    • Vancouver

      Liang Z. Brazilian Conference on Intelligent Systems (BRACIS), 7 [Internet]. 2018 ;Available from: https://bracis2018.mybluemix.net/

  • Curadoria

    Symposium on Bioinformatics and Bioforensics (SBB’18) (2018)

    Liang, Zhao

    Unidade: FFCLRP

    Subjects: BIOINFORMÁTICA, DOENÇAS

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      LIANG, Zhao. Symposium on Bioinformatics and Bioforensics (SBB’18). [S.l: s.n.], 2018.Disponível em: .

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      Liang, Z. (2018). Symposium on Bioinformatics and Bioforensics (SBB’18). Bangalore. Recuperado de http://icacci-conference.org/2018/sbb2018

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      Liang Z. Symposium on Bioinformatics and Bioforensics (SBB’18) [Internet]. 2018 ;Available from: http://icacci-conference.org/2018/sbb2018

    • Vancouver

      Liang Z. Symposium on Bioinformatics and Bioforensics (SBB’18) [Internet]. 2018 ;Available from: http://icacci-conference.org/2018/sbb2018

  • Trabalho de evento

    A network-based high level data classification technique (2018)

    Colliri, Tiago Santos; Ji, Donghong; Pan, Heng; Liang, Zhao

    Source: Annals. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC

    Subjects: REDES NEURAIS, TECNOLOGIA

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    • ABNT

      COLLIRI, Tiago Santos; JI, Donghong; PAN, Heng; LIANG, Zhao. A network-based high level data classification technique. Anais.. Rio de Janeiro: [s.n.], 2018.Disponível em: DOI: 10.1109/ijcnn.2018.8489081.

    • APA

      Colliri, T. S., Ji, D., Pan, H., & Liang, Z. (2018). A network-based high level data classification technique. In Annals. Rio de Janeiro. doi:10.1109/ijcnn.2018.8489081

    • NLM

      Colliri TS, Ji D, Pan H, Liang Z. A network-based high level data classification technique [Internet]. Annals. 2018 ;Available from: http://dx.doi.org/10.1109/ijcnn.2018.8489081

    • Vancouver

      Colliri TS, Ji D, Pan H, Liang Z. A network-based high level data classification technique [Internet]. Annals. 2018 ;Available from: http://dx.doi.org/10.1109/ijcnn.2018.8489081

  • Artigo de periodico

    Network community detection via iterative edge removal in a flocking-like system (2018)

    Verri, Filipe Alves Neto; Gueleri, Roberto Alves; Zheng, Qiusheng; Liang, Zhao

    Source: ArXiv Statistics. Unidade: FFCLRP

    Subjects: REDES COMPLEXAS, ENGENHARIA ELÉTRICA

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    • ABNT

      VERRI, Filipe Alves Neto; GUELERI, Roberto Alves; ZHENG, Qiusheng; LIANG, Zhao. Network community detection via iterative edge removal in a flocking-like system. ArXiv Statistics, Ithaca, p. 1-6, 2018. Disponível em: < https://www.researchgate.net/publication/323141978_Network_community_detection_via_iterative_edge_removal_in_a_flocking-like_system >.

    • APA

      Verri, F. A. N., Gueleri, R. A., Zheng, Q., & Liang, Z. (2018). Network community detection via iterative edge removal in a flocking-like system. ArXiv Statistics, 1-6. Recuperado de https://www.researchgate.net/publication/323141978_Network_community_detection_via_iterative_edge_removal_in_a_flocking-like_system

    • NLM

      Verri FAN, Gueleri RA, Zheng Q, Liang Z. Network community detection via iterative edge removal in a flocking-like system [Internet]. ArXiv Statistics. 2018 ; 1-6.Available from: https://www.researchgate.net/publication/323141978_Network_community_detection_via_iterative_edge_removal_in_a_flocking-like_system

    • Vancouver

      Verri FAN, Gueleri RA, Zheng Q, Liang Z. Network community detection via iterative edge removal in a flocking-like system [Internet]. ArXiv Statistics. 2018 ; 1-6.Available from: https://www.researchgate.net/publication/323141978_Network_community_detection_via_iterative_edge_removal_in_a_flocking-like_system

  • Artigo de periodico

    Network unfolding map by vertex-edge dynamics modeling (2018)

    Verri, Filipe Alves Neto; Urio, Paulo Roberto; Liang, Zhao

    Source: IEEE Transactions on Neural Networks and Learning Systems. Unidade: FFCLRP

    Subjects: REDES NEURAIS, REDES COMPLEXAS, SISTEMAS DINÂMICOS

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    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      VERRI, Filipe Alves Neto; URIO, Paulo Roberto; LIANG, Zhao. Network unfolding map by vertex-edge dynamics modeling. IEEE Transactions on Neural Networks and Learning Systems, Piscataway, v. 29, n. 2, p. 405-418, 2018. Disponível em: < http://dx.doi.org/10.1109/TNNLS.2016.2626341 > DOI: 10.1109/TNNLS.2016.2626341.

    • APA

      Verri, F. A. N., Urio, P. R., & Liang, Z. (2018). Network unfolding map by vertex-edge dynamics modeling. IEEE Transactions on Neural Networks and Learning Systems, 29( 2), 405-418. doi:10.1109/TNNLS.2016.2626341

    • NLM

      Verri FAN, Urio PR, Liang Z. Network unfolding map by vertex-edge dynamics modeling [Internet]. IEEE Transactions on Neural Networks and Learning Systems. 2018 ; 29( 2): 405-418.Available from: http://dx.doi.org/10.1109/TNNLS.2016.2626341

    • Vancouver

      Verri FAN, Urio PR, Liang Z. Network unfolding map by vertex-edge dynamics modeling [Internet]. IEEE Transactions on Neural Networks and Learning Systems. 2018 ; 29( 2): 405-418.Available from: http://dx.doi.org/10.1109/TNNLS.2016.2626341
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