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An extended discussion of modeling considerations, including alternative model architectures, is contained in the Supplemental Results.
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Although multilayer perceptrons are still the most popular model architecture, other model architectures are also used extensively.
The highest level model architectures are described in terms of modules and interconnections.
Numerous model architectures are available to approximate complex data structures, however, creating and selecting the best model provides a present challenge for application.
Distributed model architectures are widely used for automatabased fault diagnosis to ensure model completeness and to avoid the state space explosion problem.
Several model architectures were trained, with the best performance reaching a 99.53% success rate in identifying the corresponding [plant, disease] combination (or healthy plant).
Despite these differences, simulated epidemics generated under some model architectures are insensitive to the average degree of contact amongst nodes, k.
Model architectures are given in parenthesis.
Three different CAN transceiver model architectures were implemented.
The best model architecture is shown in Table 3.
The model architecture is flexible permitting updates as new data become available.
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