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@ElectronicSource{TrontoSilvAnna::ArNeNe,
             abstract = "Machine learning techniques such as neural networks, rule 
                         induction, genetic algorithm and case-based reasoning are finding 
                         application in a wide variety of fields such as computer vision, 
                         econometrics and medicine, where human abilities have proven to be 
                         superior to those of computers. Such techniques hold the promise 
                         of being able to make sense of a variety of inputs of different 
                         types in producing an output. Software effort modeling has always 
                         appeared to be a rather hit-or-miss business where statistical 
                         methods frequently result in low accuracy of prediction. Some 
                         experiments using an artificial neural networks have been 
                         conducted, highlighting some of the problems that arise when 
                         machine learning techniques are applied to software effort 
                         modeling. These experiments show that, compared with conventional 
                         regression analysis, improved accuracy of prediction is 
                         possible.",
              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, Jose Demisio Simoes da 
                         and Anna, Nilson Sant",
             keywords = "Software effort estimation, neural network model, regression 
                         analysis.",
       lastupdatedate = "2006-12-21",
            publisher = "Instituto and Nacional and de and Pesquisas and Espaciais",
                  ibi = "sid.inpe.br/ePrint@80/2006/12.20.23.38",
                  url = "http://urlib.net/rep/sid.inpe.br/ePrint@80/2006/12.20.23.38",
           targetfile = "v1.pdf",
                title = "The artificial neural networks model for software effort 
                         estimation",
         typeofmedium = "On-line",
        urlaccessdate = "16 jan. 2021"
}


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