The single hidden layer, 10 hidden nodes, 10,000 epochs, small learning rate of 0.005, and 0.15 of momentum term are applied to model the depth of anesthesia.
We found that a bulk-vascularization assumption to modeling the depth dependence of the signal does not provide an accurate picture of penetration depth of the collected fluorescence signal in most cases.
Since there are three possible v', the existence probability of v' (probability of branching at u) is In order to estimate the value of depth x, we use a multi-normal distribution to model the depth distribution of a component as there can be multiple isoforms, say t, in a component.
However this simple one-parameter model failed to model the crater depth adequately.
Using these models and a digital elevation model, the depth to sulfides could be adequately predicted.
Using a thin-film model, the depth of the degraded layer and its mechanical properties are also extracted.
Based on the proposed model, the depth of extraneous fluid invasion can be determined when the operation conditions, extraneous fluid properties and formation structure parameters are available, and the model predictions are in good agreement with the available data.
Mixed model means combining these 2D models with the depth saliency models proposed by [14] (denoted as 2D × depth (Chamaret)) and [17] (which have two models denoted as 2D + depth contrast and 2D + DSM).
