Latin-American Journal of Computing (LAJC)

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  Año 2024, Vol. 11, Número 2

  • Research Articles for the Regular Issue

    • Editorial

      Gabriela Suntaxi (LAJC)

      • Resumen
      • Texto completo

      págs. 8-10

      

    • Exploring Digital Twins of Nonlinear Systems through Meta-Modeling with Echo State Networks

      Laisa Cristina Juffo Cristina Juffo Campos, Ana Carolina Spindola Rangel Dias, Wellington Betencurte da Silva, Julio Cesar Sampaio Dutra

      • Resumen
      • Texto completo

      págs. 13-22

      

    • Estimation of Spatially Dependent Coefficients in Heterogeneous Media in Diffusive Heat Transfer Problems

      Lucas Lopes da Silva Costa, Eduardo Cunha Classe, Lucas da Silva Asth, Luiz Alberto da Silva Abreu, Diego Campos Knupp, Leonardo Tavares Stutz

      • Resumen
      • Texto completo

      págs. 23-32

      

    • Forensic Investigation in Robots

      Tharmini Janarthanan, Shahrzad Zargari

      • Resumen
      • Texto completo

      págs. 33-40

      

    • ANN-MoC Method for Inverse Transient Transport Problems in One-Dimensional Domain

      Nelson Garcia Roman, Pedro Costas dos Santos, Pedro Henrique de Almeida Konzen

      • Resumen
      • Texto completo

      págs. 41-50

      

    • A study on the impact of data balance on rainfall prediction through artificial neural networks using surface microwave radiometers

      Lourenço José Cavalcante Neto, Alan James Peixoto Calheiros

      • Resumen
      • Texto completo

      págs. 51-59

      

    • Classification of Failure Using Decision Trees Induced by Genetic Programming

      Rogério Costa Negro Rocha, Laércio Ives Santos, Rafael Almeida Soares, Franciele Alves Barbosa, Marcos Flávio Silveira Vasconcelos D’Angelo

      • Resumen
      • Texto completo

      págs. 60-69

      

    • A Comparative Study Between the Brazilian Stock Market and Cryptocurrencies

      Marjori Klinczak, Egon Wildauer

      • Resumen
      • Texto completo

      págs. 70-79

      

    • Electricity Energy Demand Prediction Using Computational Intelligence Techniques

      Camila Martins Saporetti, Bruno da S. Macêdo

      • Resumen
      • Texto completo

      págs. 80-88