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@ElectronicSource{TrontoSilvSant::CoArNe,
             abstract = "Estimating development effort remains a complex problem attracting 
                         considerable research attention. Improving the estimation 
                         techniques available to project managers would facilitate more 
                         effective control of time and budgets in software development. In 
                         this paper, predictive Artificial Neural Network and regression 
                         based models are investigated, comparing the performance of both 
                         methods. The results show that ANNs are effective in effort 
                         estimation.",
              address = "S{\~a}o Jos{\'e} dos Campos",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
               author = "Tronto, Iris Fabiana de Barcelos and Silva, Jos{\'e} 
                         Dem{\'{\i}}sio Sim{\~o}es da and Sant'Anna, Nilson",
             keywords = "software effort, artificial neural network, regression analysis, 
                         software development estimate.",
       lastupdatedate = "2006-12-09",
            publisher = "Instituto and Nacional and de and Pesquisas and Espaciais",
                  ibi = "sid.inpe.br/ePrint@80/2006/12.08.12.47",
                  url = "http://urlib.net/rep/sid.inpe.br/ePrint@80/2006/12.08.12.47",
           targetfile = "v1.pdf",
                title = "Comparison of Artificial Neural Network and Regression Models in 
                         Software Effort Estimation",
         typeofmedium = "On-line",
        urlaccessdate = "16 jan. 2021"
}


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