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To validate the performance of the method in handling fiber-matrix material models, we perform a second study on dilating a long fiber-reinforced tube.
To assess the predictive strength of our models, we perform a stratified threefold cross validation.
Based on the forecast of the models, we perform simulated trading and record the profits or losses by comparing the predicted price movement with the actual price movement.
To further test the generalization of our models, we perform cross-dataset experiments where we test on two other publicly available datasets: UT-Interaction and SBU Kinect.
In order to compare both models, we perform numerical simulations under homogeneous conditions and compare the spatiotemporal dynamics of the action potential waves.
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To validate the models we performed three experiments.
To validate and assess our models we performed tenfold cross-validation and nested cross-validation protocols.
For both models, we performed nondimensionalization to identify possible groupings of variables into classes corresponding to they timescales on which they evolve.
In order to validate accurately the statistical models we performed the nested cross-validation protocol as described by Ruschhaupt et al. [20].
Given the high similarity detected between both final models, we performed the variation partitioning procedure on one of them only.
To check the robustness of our models, we performed several sensitivity analyses.
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