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Software development effort prediction of industrial projects applying a general regression neural network
(2012)
An important factor for planning, budgeting and bidding a software project is prediction of the development effort required to complete it. This prediction can be obtained from models related to neural networks. The ...
Previsão do índice bursatil IBEX 35 usando redes neurais artificiais
(Universidade Estadual Paulista (Unesp), 2021-04-09)
A previsão de índices bolsistas de diferentes bolsas de valores é uma das questões mais importantes para economistas e investidores, a fim de conhecer, antecipadamente, os movimentos que ocorrem no mercado de investimento. ...
Previsão de carga multinodal utilizando redes neurais de regressão generalizada
(Universidade Estadual Paulista (UNESP), 2014)
Simultaneous determination of lead and sulfur by energy-dispersive x-ray spectrometry. Comparison between artificial neural networks and other multivariate calibration methods
(John Wiley & Sons LtdW SussexInglaterra, 1999)
FEMaR: A finite element machine for regression problems
(2017-06-30)
Regression-based tasks have been the forerunner regarding the application of machine learning tools in the context of data mining. Problems related to price and stock prediction, selling estimation, and weather forecasting ...
FEMaR: A Finite Element Machine for Regression Problems
(Ieee, 2017-01-01)
Regression-based tasks have been the forerunner regarding the application of machine learning tools in the context of data mining. Problems related to price and stock prediction, selling estimation, and weather forecasting ...
Software development effort estimation in academic environments applying a general regression neural network involving size and people factors
(2011)
In this research a general regression neural network (GRNN) was applied for estimating the development effort in software projects that have been developed in laboratory learning environments. The independent variables of ...
A neutron spectrum unfolding code based on generalized regression artificial neural networks
(Elsevier, 2016-04-30)
The most delicate part of neutron spectrometry, is the unfolding process. The derivation of the spectral
information is not simple because the unknown is not given directly as a result of the measurements.
Novel methods ...
A comparison of back propagation and Generalized Regression Neural Networks performance in neutron spectrometry
(Elsevier, 2016-04-19)
The process of unfolding the neutron energy spectrum has been subject of research for many years.
Monte Carlo, iterative methods, the bayesian theory, the principle of maximum entropy are some of the
methods used. The ...