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dc.contributor.authorSingh, J-
dc.contributor.authorSahoo, Bibhudatta-
dc.identifier.citationIJCA Special Issue on 2nd National Conference- Computing, Communication and Sensor Network (CCSN) (4):13-17, 2011. Published by Foundation of Computer Science, New York, USA.en
dc.descriptionCopyright belongs to International Journal of Computer Applicationsen
dc.description.abstractFailures of software are mainly due to the faulty project management practices, which includes effort estimation. Continuous changing scenarios of software development technology makes effort estimation more challenging. Ability of ANN(Artificial Neural Network) to model a complex set of relationship between the dependent variable (effort) and the independent variables (cost drivers) makes it as a potential tool for estimation. This paper presents a performance analysis of different ANNs in effort estimation. We have simulated four types of ANN created by MATLAB10 NNTool using NASA dataseten
dc.format.extent785811 bytes-
dc.publisherFoundation of Computer Science, USAen
dc.subjectEffort Estimationen
dc.subjectArtificial Neural Networken
dc.titleSoftware Effort Estimation with Different Artificial Neural Networken
Appears in Collections:Journal Articles

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