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  • In: 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, Nature, 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
  • Unidades: FFCLRP, EP, EESC, IFSC, IQSC

    Subjects: Matemática Aplicada, Neurociências, Física Computacional

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      LIANG, Zhao; SILVA, José Reinaldo; PROENÇA, Sérgio Persival Baroncini; et al. Conferência Brasileira de Dinâmica, Controle e Aplicações - DINCON 2019. [S.l: s.n.], 2019.Disponível em: .
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      Liang, Z., Silva, J. R., Proença, S. P. B., Asada, E. N., Maia, L. P., Varela, H., 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, Silva JR, Proença SPB, Asada EN, Maia LP, Varela H, Costa L da F, Koberle R. Conferência Brasileira de Dinâmica, Controle e Aplicações - DINCON 2019 [Internet]. 2019 ;Available from: http://143.107.182.36/dincon2019/index.php/comite-cientifico/
    • Vancouver

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

    Subjects: Redes Complexas, Aprendizado Computacional, Otimização Matemática

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      CARNEIRO, Murillo G.; CHENG, Ran; ZHAO, Liang; JIN, Yaochu. Particle swarm optimization for network-based data classification. Neural Networks, Oxford, v. 110, p. 243-255, 2019. Disponível em: < http://dx.doi.org/10.1016/j.neunet.2018.12.003 > DOI: 10.1016/j.neunet.2018.12.003.
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      Carneiro, M. G., Cheng, R., Zhao, L., & Jin, Y. (2019). Particle swarm optimization for network-based data classification. Neural Networks, 110, 243-255. doi:10.1016/j.neunet.2018.12.003
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      Carneiro MG, Cheng R, Zhao L, Jin Y. Particle swarm optimization for network-based data classification [Internet]. Neural Networks. 2019 ; 110 243-255.Available from: http://dx.doi.org/10.1016/j.neunet.2018.12.003
    • Vancouver

      Carneiro MG, Cheng R, Zhao L, Jin Y. Particle swarm optimization for network-based data classification [Internet]. Neural Networks. 2019 ; 110 243-255.Available from: http://dx.doi.org/10.1016/j.neunet.2018.12.003
  • In: 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
  • In: 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, Nature, 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.
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      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
  • In: Proceedings. Conference title: 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.
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      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
  • In: Proceedings. Conference title: 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.
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      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
  • In: 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
  • In: Journal of Applied Nonlinear Dynamics. Unidades: FFCLRP, ICMC

    Subjects: Partículas (física Nuclear), Aprendizado Computacional, Redes Neurais

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      VERRI, Filipe Alves Neto; URIO, Paulo Roberto; ZHAO, Liang. Advantages of edge-centric collective dynamics in machine learning tasks. Journal of Applied Nonlinear Dynamics, Glen Carbon, v. 7, n. 3, p. 269-285, 2018. Disponível em: < http://dx.doi.org/10.5890/jand.2018.09.005 > DOI: 10.5890/jand.2018.09.005.
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      Verri, F. A. N., Urio, P. R., & Zhao, L. (2018). Advantages of edge-centric collective dynamics in machine learning tasks. Journal of Applied Nonlinear Dynamics, 7( 3), 269-285. doi:10.5890/jand.2018.09.005
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      Verri FAN, Urio PR, Zhao L. Advantages of edge-centric collective dynamics in machine learning tasks [Internet]. Journal of Applied Nonlinear Dynamics. 2018 ; 7( 3): 269-285.Available from: http://dx.doi.org/10.5890/jand.2018.09.005
    • Vancouver

      Verri FAN, Urio PR, Zhao L. Advantages of edge-centric collective dynamics in machine learning tasks [Internet]. Journal of Applied Nonlinear Dynamics. 2018 ; 7( 3): 269-285.Available from: http://dx.doi.org/10.5890/jand.2018.09.005
  • Unidade: FFCLRP

    Subjects: Redes De Computadores

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      ZHAO, Liang. International Conference on Computing and Network Communications - CoCoNet, 2. [S.l: s.n.], 2018.Disponível em: .
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      Zhao, L. (2018). International Conference on Computing and Network Communications - CoCoNet, 2. Astana. Recuperado de http://coconet-conference.org/2018/?q=node/12
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      Zhao L. International Conference on Computing and Network Communications - CoCoNet, 2 [Internet]. 2018 ;Available from: http://coconet-conference.org/2018/?q=node/12
    • Vancouver

      Zhao L. International Conference on Computing and Network Communications - CoCoNet, 2 [Internet]. 2018 ;Available from: http://coconet-conference.org/2018/?q=node/12
  • 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
  • In: Annals. Conference title: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC

    Subjects: Redes Neurais, Tecnologia

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

    Subjects: Redes Complexas, Engenharia Elétrica

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      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 >.
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      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
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      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
  • In: IEEE Transactions on Neural Networks and Learning Systems. Unidade: FFCLRP

    Subjects: Redes Neurais, Redes Complexas, Sistemas Dinâmicos

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      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.
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      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
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      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
  • In: Proceedings. Conference title: IEEE Congress on Evolutionary Computation - CEC. Unidades: FFCLRP, ICMC

    Subjects: Ciência Da Computação, Redes De Computadores, Algoritmos Genéticos

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      VERRI, Filipe Alves Neto; TINÓS, Renato; LIANG, Zhao. Feature learning in feature–sample networks using multi-objective optimization. Proceedings[S.l: s.n.], 2018.Disponível em: DOI: 10.1109/CEC.2018.8477891.
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      Verri, F. A. N., Tinós, R., & Liang, Z. (2018). Feature learning in feature–sample networks using multi-objective optimization. Proceedings. Piscataway. doi:10.1109/CEC.2018.8477891
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      Verri FAN, Tinós R, Liang Z. Feature learning in feature–sample networks using multi-objective optimization [Internet]. Proceedings. 2018 ;Available from: https://doi.org/10.1109/CEC.2018.8477891
    • Vancouver

      Verri FAN, Tinós R, Liang Z. Feature learning in feature–sample networks using multi-objective optimization [Internet]. Proceedings. 2018 ;Available from: https://doi.org/10.1109/CEC.2018.8477891
  • In: Annals. Conference title: International Joint Conference on Neural Networks (IJCNN). Unidade: FFCLRP

    Subjects: Redes Complexas

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      ANGHINONI, Leandro; LIANG, Zhao; ZHENG, Qiusheng; ZHANG, Junbao. Time series trend detection and forecasting using complex network topology analysis. Anais.. Rio de Janeiro: [s.n.], 2018.Disponível em: DOI: 10.1109/ijcnn.2018.8489167.
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      Anghinoni, L., Liang, Z., Zheng, Q., & Zhang, J. (2018). Time series trend detection and forecasting using complex network topology analysis. In Annals. Rio de Janeiro. doi:10.1109/ijcnn.2018.8489167
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      Anghinoni L, Liang Z, Zheng Q, Zhang J. Time series trend detection and forecasting using complex network topology analysis [Internet]. Annals. 2018 ;Available from: http://dx.doi.org/10.1109/ijcnn.2018.8489167
    • Vancouver

      Anghinoni L, Liang Z, Zheng Q, Zhang J. Time series trend detection and forecasting using complex network topology analysis [Internet]. Annals. 2018 ;Available from: http://dx.doi.org/10.1109/ijcnn.2018.8489167
  • In: Expert Systems with Applications. Unidade: FFCLRP

    Subjects: Aprendizado Computacional, Gestão Da Informação, Passeios Aleatórios

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      CUPERTINO, Thiago Henrique; CARNEIRO, Murillo Guimarães; QIUSHENG, Zheng; JUNBAO, Zhang; LIANG, Zhao. A scheme for high level data classification using random walk and network measures. Expert Systems with Applications, Elmsford, v. 92, p. 289-303, 2018. Disponível em: < http://dx.doi.org/10.1016/j.eswa.2017.09.014 > DOI: 10.1016/j.eswa.2017.09.014.
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      Cupertino, T. H., Carneiro, M. G., Qiusheng, Z., Junbao, Z., & Liang, Z. (2018). A scheme for high level data classification using random walk and network measures. Expert Systems with Applications, 92, 289-303. doi:10.1016/j.eswa.2017.09.014
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      Cupertino TH, Carneiro MG, Qiusheng Z, Junbao Z, Liang Z. A scheme for high level data classification using random walk and network measures [Internet]. Expert Systems with Applications. 2018 ; 92 289-303.Available from: http://dx.doi.org/10.1016/j.eswa.2017.09.014
    • Vancouver

      Cupertino TH, Carneiro MG, Qiusheng Z, Junbao Z, Liang Z. A scheme for high level data classification using random walk and network measures [Internet]. Expert Systems with Applications. 2018 ; 92 289-303.Available from: http://dx.doi.org/10.1016/j.eswa.2017.09.014
  • In: IEEE Transactions on Evolutionary Computation. Unidade: FFCLRP

    Subjects: Algoritmos Genéticos, Clusters

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      TINÓS, Renato; ZHAO, Liang; CHICANO, Francisco; WHITLEY, Darrell. NK hybrid genetic algorithm for clustering. IEEE Transactions on Evolutionary Computation, Piscataway, v. 22, n. 5, p. 748-761, 2018. Disponível em: < http://dx.doi.org/10.1109/tevc.2018.2828643 > DOI: 10.1109/tevc.2018.2828643.
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      Tinós, R., Zhao, L., Chicano, F., & Whitley, D. (2018). NK hybrid genetic algorithm for clustering. IEEE Transactions on Evolutionary Computation, 22( 5), 748-761. doi:10.1109/tevc.2018.2828643
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      Tinós R, Zhao L, Chicano F, Whitley D. NK hybrid genetic algorithm for clustering [Internet]. IEEE Transactions on Evolutionary Computation. 2018 ; 22( 5): 748-761.Available from: http://dx.doi.org/10.1109/tevc.2018.2828643
    • Vancouver

      Tinós R, Zhao L, Chicano F, Whitley D. NK hybrid genetic algorithm for clustering [Internet]. IEEE Transactions on Evolutionary Computation. 2018 ; 22( 5): 748-761.Available from: http://dx.doi.org/10.1109/tevc.2018.2828643
  • In: Proceedings. Conference title: International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery - ICNC-FSKD. Unidades: ICMC, FFCLRP

    Subjects: Redes Complexas, Aprendizado Computacional, Reconhecimento De Padrões

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      CARNEIRO, Murilo G; ROSA, João Luís Garcia; QIUSHENG, Zheng; XIAOMING, Liu; LIANG, Zhao. Improving semantic role labeling using high-level classification in complex networks. Anais.. Los Alamitos: IEEE, 2017.Disponível em: DOI: 10.1109/FSKD.2017.8393113.
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      Carneiro, M. G., Rosa, J. L. G., Qiusheng, Z., Xiaoming, L., & Liang, Z. (2017). Improving semantic role labeling using high-level classification in complex networks. In Proceedings. Los Alamitos: IEEE. doi:10.1109/FSKD.2017.8393113
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      Carneiro MG, Rosa JLG, Qiusheng Z, Xiaoming L, Liang Z. Improving semantic role labeling using high-level classification in complex networks [Internet]. Proceedings. 2017 ;Available from: http://dx.doi.org/10.1109/FSKD.2017.8393113
    • Vancouver

      Carneiro MG, Rosa JLG, Qiusheng Z, Xiaoming L, Liang Z. Improving semantic role labeling using high-level classification in complex networks [Internet]. Proceedings. 2017 ;Available from: http://dx.doi.org/10.1109/FSKD.2017.8393113


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