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In recent years, these types of systems have become increasingly powerful with regards to modeling accuracy; however, many of these improvements come at the cost of model interpretability.
Based on these relationships, the total cost of model can be expressed as a function of product tolerance from which the optimal tolerance limits can be found out.
In the second approach, after locating precisely the eventual damage of a structure using modal strain energy based index (MSEBI), to efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, the MSEBI of structural elements is evaluated using a properly trained surrogate model.
The cost of model development is assumed flat across all instances, so (c_{mathrm{Model}}) is the total cost of model development divided by the number of instances in the training data.
The cost of model development can be the human resources expended towards model development as well as possible computational cost.
Added to this cost, is the cost of whatever strategy is in effect — cost of external data, cost of model development, etc.
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This could add up to $1,500 to the cost of models like the Lincoln Navigator, on which profit margins approach $15,000.
To balance the contradiction between comprehensiveness of system-of-systems (SoS) description and cost of modeling and simulation, a non-uniform hybrid strategy (NUHYS) is proposed.
However, the cost of modeling such characters, authoring and editing their interactions, and delivering them over limited-bandwidth connections can be prohibitive.
The computational cost of modeling the languages can be considered equal to the baseline.
And let c φ denote the computation cost of the mapping from x to φ(x), and cmodeling(F,M) denotes the computational cost of modeling the languages, which relate to F and M.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com