García Crespo, ÁngelColomo Palacios, RicardoLópez-Cuadrado, José LuisRuiz Mezcua, María Belén2012-06-062012-06-062011-06-16IEEE Latin America Transactions , (June 2011), 9(3), 384-398.1548-0992https://hdl.handle.net/10016/14478One of the most important tasks of a software development project manager is to produce accurate time and effort estimations. Improving the estimation accuracy is a widely recognized benefit for several software development processes. In order to achieve these objectives, there are proposals based on Artificial Intelligence techniques and specifically artificial neural networks. This paper proposes an optimization methodology for searching the best neural model applicable to the effort estimation of software projects. This will draw on a set of known factors in the early stages of development, outside the complex calculation of function points, which would entail a high level of maturity and definition of the project. This methodology has allowed, on the one hand, ensure the adequacy of the proposed neural network model and, on the other hand, optimize the performance, both in time and accuracy.application/pdfeng© IEEENeural networksSoftware engineeringEffort estimationOptimization methodologyresearch articleInformática10.1109/TLA.2011.5893788open access3843398IEEE Latin America Transactions9