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However, the neural network in generalized regression structure fit line approaches the ideal line closer than neural network in back propagation structure fit line (Fig. 4a, b).
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We explain the term structure of crude oil prices using the dynamic Nelson Siegel model and propose to forecast oil prices using a generalized regression framework based on neural networks.
Or adultesence might be just the opposite: not evidence of progress but another sign of a generalized regression.
generalized regression neural network.
The generalized regression techniques thus obtained are usually called projection pursuit regression (PPR) methods.
Probit models and logistic regression models both belong to the generalized regression model family.
Initially, three single-stage models were designed, namely the generalized regression neural network, feedforward neural network and multiple linear regression.
For comparison purposes, multivariable regression and generalized regression neural networks were used for E and UCS prediction.
After that, a generalized regression neural network (GRNN) is used for fault classification.
A generalized regression model is also provided by combining the available data of any cross-section.
Using results from our simulations, generalized regression equations are fitted to obtain steady-state hospital capacities.
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