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Enhanced phenomenological consistency and immunity against overfitting of the MLP model were achieved by embedding specific domain prior knowledge.
A theoretical model is developed and validated against experimental data, where good agreement between the measured values and those calculated by the simulation model were achieved.
Absolute fraction of variance and root mean square error of 0.99 and 0.008, in training and testing phases of the model were achieved showing the relatively high accuracy of the proposed ANFIS model.
Absolute fraction of variance, absolute percentage error and root mean square error of 0.94, 11.52 and 14.48, respectively in training phase and 0.92, 15.89 and 23.69, respectively in testing phase of the model were achieved showing the relatively high accuracy of the proposed ANFIS model.
Two independent runs for each model were achieved for 30000000 steps and sampled every 1000 steps.
The all possible functions of age and height as well as the interactions of which were considered in the modeling, the most fitted model were achieved.
Similar(53)
The validation of the model is achieved through comparing the modeling results with CMG simulators and Buckley Leverett theory.
The solution of this model is achieved using implicit scheme.
Thus the entire model is achieved in a recursive manner.
A good generalization performance of the model is achieved.
In this way, the damage model is achieved.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com