@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/ibi/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 = "27 abr. 2024"
}