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This means that the neural network in generalized regression scheme estimate porosity better than the neural network in back propagation scheme.
As it can be seen in Figs. 6, 7 and 8, neural network in generalized regression scheme is in better concordance with observed porosity values as compared to the neural network in back propagation scheme.
From all the results in this study we see that, neural network generalized regression scheme is better than neural network in back propagation scheme.
A visual check in Table 2, clearly depicts that neural network generalized regression scheme surpasses neural network in back propagation scheme since, GRNN scheme produces higher R 2 and r values and lower MSE value, while FFBP scheme suffers from lower R 2 and r values and higher MSE value.
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To overcome the above problems, a new motion control scheme with deadzone estimation and compensation using generalized regression neural network (GRNN) is proposed in this paper to improve the control performance of the TWUSM drive system.
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.
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