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The proposed hybrid modelling architecture is validated in the field of rotating machinery using time-domain and frequency-domain analysis.

Web-based distributed modelling architectures are gaining increasing recognition as potentially useful tools to build holistic environmental models, combining individual components in complex workflows.

The four major issues highlighted by this intricate set of simulations, using a remarkably flexible and extendable modeling architecture, are as follows.

The best model architecture is shown in Table 3.

The model architecture is flexible permitting updates as new data become available.

Next, the proposed models architecture is discussed in "The proposed model" section with full details about the model's components, inputs and outputs.

Each model architecture is estimated k = 20 times, and because there are eight different neural network-based model architecture to be estimated in the study, the total number of estimated models is 160; whereas, the selected 8 models (based on the lowest MSE error criteria) will be reported in the study.

The detailed model architecture is illustrated in Figure 3.

An overview of the model architecture is depicted in Figure 2. The first component comprises initial feedforward processing.

Our model architecture is inspired by biological mechanisms and is based on neural representations of early visual cortex.

A graphical overview of our model architecture is depicted in Fig. 1.