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		<citationkey>TrontoSilvSant::CoArNe</citationkey>
		<title>Comparison of Artificial Neural Network and Regression Models in Software Effort Estimation</title>
		<lastupdatedate>2006-12-09</lastupdatedate>
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		<author>Tronto, Iris Fabiana de Barcelos,</author>
		<author>Silva, José Demísio Simões da,</author>
		<author>Sant'Anna, Nilson,</author>
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		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<electronicmailaddress>iris_barcelos@lac.inpe.br</electronicmailaddress>
		<electronicmailaddress>demisio@lac.inpe.br</electronicmailaddress>
		<electronicmailaddress>nilson@lac.inpe.br</electronicmailaddress>
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		<city>São José dos Campos</city>
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		<keywords>software effort, artificial neural network, regression analysis, software development estimate.</keywords>
		<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.</abstract>
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