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The proposed fuzzy modeling for measurement condition estimation contains three steps as shown in Figure 2: (1) fuzzy model parameter preparation, (2) probability-possibility transformation, and (3) measurement condition estimation.
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The influence of the model parameters and preparation conditions, on the properties of the polymer and film and their development during reaction, have been studied.
Details of the reference model and a thorough exploration of the model parameter space will be published elsewhere (Hu et al., manuscript in preparation).
Model parameter selection will become increasingly automated — model deployment entirely so.
Kinetic model parameter descriptions.
Laplacian Model Parameter Estimation.
Cauchy Model Parameter Estimation.
Each weight represents a free model parameter.
Estimating model parameter differences.
Therefore, model parameter C and kernel parameter γ are required.
In this module, DBN stacked by a number of RBMs is built and then trained by training dataset from data preparation module to obtain the model parameters.
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