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An artificial neural network (ANN) based model is considered to be a powerful subsidiary tool of high fidelity models for its fast computational speed and reliable prediction capability.
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Six corresponding-states based models were considered for comparison, the lowest overall deviation being 3.7%.
When these kernel based models are considered, RVM model found successful in terms of statistical performance criterions (e.g., performance index, PI values for training and testing data are computed as 1.579 and 1.449).
Each state-based model is considered as an abstraction, which is more or less close to the target algorithmic entity.
Specifically, we use ONE's default setting, whereby in the first group of experiments, the shortest map-based model is considered in a 5 × 3 km2area of downtown Helsinki, Finland.
The event-based model is considered ineffective [37, 41, 50, 51], additionally contributing to inappropriateness, as only written information is provided and this does not necessarily imply that patients are truly informed about the risks and benefits of the examination and potential alternatives [52, 53].
The hypergraph-based model is considered as a population of hyperedges.
Furthermore, an effectiveness-NTU method based model is developed by considering the constraint of the total thermal conductance.
Whereas the agent architecture is described in the form of frame-like structures, a tri-base acquaintance model is considered to formalise the negotiation and control processes.
In this paper, the variance reduction for particle Monte Carlo simulations based on the Fokker Planck model is considered.
A coupled orbit-attitude dynamic model is considered based on the specific configuration of atmospheric-based actuators.
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