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G P(D) is a random function which functional values follow a centered Gaussian distribution for any set of datapoints.
In fact, we will use a similar architecture of dictionaries with string-valued keys and functional values to implement an object-oriented system later in this chapter.
A quadratic polynomial without cross terms is adopted to parameterize the black-box limit-state function, based on which the functional values as well as the first-order gradients can be explicitly calculated.
The evaluator is not going to produce functional values.
Functional values are plotted for each participant for the learning-period (triangle) and the post-learning period (circle).
Furthermore, we review the susceptibility of each habitat to disturbances to investigate spatial patterns that might affect functional values.
We provide examples of mapping the functional values of habitats for populations of three commercially important species.
The locally optimal solutions with the lower objective functional values are retained and the locally optimal solutions with the higher objective functional values are discarded.
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All the parameters considered in our study showed highly significant difference in pre-treatment and post-functional values, suggesting their reliability (p < 0.0001).
Non-functional values of T i are printed in red.
Non-functional values of τ are printed in red.
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CEO of Professional Science Editing for Scientists @ prosciediting.com