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A model updating strategy for predicting time series with seasonal patterns
(ELSEVIER, 2010)
Traditional methodologies for time series prediction take the series to be predicted and split it into Q1
training, validation, and test sets. The first one serves to construct forecasting models, the second set for
model ...
Using model updating technique to train neural network for fault detection
(1997-01-01)
Vibration monitoring and fault detection of components in manufacturing plants involve a detailed analysis of a collection of vibration data in order to establish a correlation among changes of the measured data and the ...
Nonlinear updating method: a review
(2017-11-01)
This paper is a survey of the literature about the nonlinear updating process. It is focused on the computation of the difference between the numerical model and the reference data as well as the algorithm uses to find the ...
Understanding the Implications of View Update Policies
(SpringerNew YorkEUA, 1986)
Detecção de pistas de aeroporto em imagens orbitais utilizando morfologia matemática
(2005-01-01)
The Brazilian Cartography presents great deficiency in cartographic products updating. This form, Remote Sensins techniques together Digital Processing Images - DPI, are contributing to improve this problem. The Mathematical ...
Detecção de pistas de aeroporto em imagens orbitais utilizando morfologia matemática
(2005-01-01)
The Brazilian Cartography presents great deficiency in cartographic products updating. This form, Remote Sensins techniques together Digital Processing Images - DPI, are contributing to improve this problem. The Mathematical ...
Update in Gynecology and Obstetrics: reviews and databases
(SPRINGER HEIDELBERG, 2008)
There is a considerable body of new information on Gynecology and Obstetrics. To aid in keeping gynecologists updated, renowned periodicals publish review articles. Review articles enable the reader to obtain the best ...
Binarization algorithms for approximate updating in credal nets
(Ios Press, 2006)
Credal networks generalize Bayesian networks relaxing numerical parameters. This considerably expands expressivity. but makes belief updating a hard task even on polytrees. Nevertheless, if all the variables are binary, ...