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@InProceedings{TrontoSilvSant:2007:CoArNe,
               author = "Tronto, Iris Fabiana Barcelos and Silva, Jos{\'e} Demisio 
                         Sim{\~o}es da and Sant'Anna, Nilson",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Comparison of Artificial Neural Network and Regression Models in 
                         Software Effort Estimation",
            booktitle = "Proceedings...",
                 year = "2007",
         organization = "International Joint Conference on Neural Networks, (IJCNN).",
             abstract = "Good practices in software project management are basic 
                         requirements for companies to stay in the market, because the 
                         effective project management leads to improvements in product 
                         quality and cost reduction. Fundamental measurements are the 
                         prediction of size, effort, resources, cost and time spent in the 
                         software development process. In this paper, predictive Artificial 
                         Neural Network (ANN) and Regression based models are investigated, 
                         aiming at establishing simple estimation methods alternatives. The 
                         results presented in this paper compare the performance of both 
                         methods and show that artificial neural networks are effective in 
                         effort estimation.",
  conference-location = "Orlando, Fl{\'o}rida",
      conference-year = "12-17 Apr.",
             language = "en",
           targetfile = "tronto_comparison.pdf",
        urlaccessdate = "16 jan. 2021"
}


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