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Increased understanding from the models can lead to improvements in equipment design and operation, potentially leading to large increases in equipment and process efficiency, throughput and/or product quality.
The over-simplifications in various existing material models can lead to incorrect predictions.
Sometimes, different models can lead to different relationships between performers, audiences and venues that are built on something other than a monetary exchange for a commodity.
This study showed that coupling ANN with semi-distributed models can lead to improved daily streamflow predictions in ungauged watersheds.
The utility of such models is that equating drag and thrust models can lead to reduced–order equations to obtain the swimming velocity of the animal11.
Here we see how different drag models can lead to different values of the ratio of drag power to muscle power.
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This model can lead to several different distributed versions.
The recombinational model can lead to homoploid hybrid speciation under conditions that promote isolation of derived lineages.
An inaccurate model can lead to erroneous inversion of contaminant sources.
Measurement errors in explanatory variables of a CF model can lead to unreliable estimates of certain parameters.
As this kind of model can lead to computationally intensive simulations, a parallelization on a distributed memory architecture was developed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com