@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 = "27 abr. 2024"
}