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Since all the complex form of (1) can be written as (3), we assume that (1) is a real-valued model without loss of generality in the following.
Since a linear kernel can be substituted for nonlinear ones in our hybrid model without loss of accuracy, our model is scalable and computationally efficient.
Therefore, a proper representation of their overall mechanical properties requires developing multiscale schemes capable of describing the behavior of the discrete system with a continuum model without loss of essential microstructural details.
Our method combines the sequential de-noising and the classification aspects in one integrated supervised architecture, so that they can cooperatively learn a better overall predictive model, without loss of relevant signal to either.
It turned out that this feedback loop, which is of clear importance for the ODE model, can be dropped in the hybrid model without loss of accuracy for the scenarios considered (see Discussion).
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5) The electric power flows are modeled through a DC flow model without losses, which takes into account the available transmission capacity imposed by the network and other operational constraints.
The Marginal model, with non-weighted fit, displays a bias for smoking similar to the same model without losses.
The features selected from the signals can be further processed in order to limit the size of the Neural Network models without loss of information.
A case study is performed and the results prove that the simplified approach can simplify Markov modeling without loss of accuracy if a proper common cause failure (CCF) model is adopted.
Therefore the attributes can be encoded by a single attribute with a finite range, and we will restrict our attention to this class of models without loss of generality.
To validate the feasibility of our model and without loss of generality, the conversion of Data Flow Diagrams DFDD) objects into Gantt and Pert diagrams is demonstrated in this study.
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