%0 Conference Proceedings
%4 sid.inpe.br/mtc-m17@80/2007/11.28.16.53
%2 sid.inpe.br/mtc-m17@80/2007/11.28.16.53.19
%T Comparison of Artificial Neural Network and Regression Models in Software Effort Estimation
%D 2007
%A Tronto, Iris Fabiana Barcelos,
%A Silva, José Demisio Simões da,
%A Sant'Anna, Nilson,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress iris_barcelos@lac.inpe.br
%@electronicmailaddress demisio@lac.inpe.br
%@electronicmailaddress nilson@lac.inpe.br
%B International Joint Conference on Neural Networks, (IJCNN).
%C Orlando, Flórida
%8 12-17 Apr.
%S Proceedings
%X 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.
%@language en
%3 tronto_comparison.pdf