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Filtros : "Financiado pela PRP USP" "COLLIRI, TIAGO SANTOS" Removidos: "FE-EDA" "UMESP" 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

    Fonte: Natural Computing. Unidades: FFCLRP, ICMC

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

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    • ABNT

      COLLIRI, Tiago Santos e LIANG, Zhao. Stock market trend detection and automatic decision-making through a network-based classification model. Natural Computing, v. 20, n. 4, p. 791-804, 2021Tradução . . Disponível em: https://doi.org/10.1007/s11047-020-09829-9. Acesso em: 29 ago. 2024.

    • APA

      Colliri, T. S., & Liang, Z. (2021). Stock market trend detection and automatic decision-making through a network-based classification model. Natural Computing, 20( 4), 791-804. doi:10.1007/s11047-020-09829-9

    • NLM

      Colliri TS, Liang Z. Stock market trend detection and automatic decision-making through a network-based classification model [Internet]. Natural Computing. 2021 ; 20( 4): 791-804.[citado 2024 ago. 29 ] 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 ; 20( 4): 791-804.[citado 2024 ago. 29 ] Available from: https://doi.org/10.1007/s11047-020-09829-9

  • Artigo de periodico

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

    Colliri, Tiago Santos ; Liang, Zhao

    Fonte: Scientific Reports. Unidades: FFCLRP, ICMC

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

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

    • ABNT

      COLLIRI, Tiago Santos e LIANG, Zhao. Analyzing the Bills-Voting dynamics and predicting corruption-convictions among brazilian congressmen through temporal networks. Scientific Reports, v. No 2019, p. 16754-1-16754-11, 2019Tradução . . Disponível em: https://doi.org/10.1038/s41598-019-53252-9. Acesso em: 29 ago. 2024.

    • 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

    • NLM

      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.[citado 2024 ago. 29 ] 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.[citado 2024 ago. 29 ] Available from: https://doi.org/10.1038/s41598-019-53252-9
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