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To accomplish this, we use the cost function as formulated in [5].
In our experiments, we use the cost function defined by frac{dgamma(t)}{dt}=kcdotgamma(t)left 1-frac{gamma(t)}{tau}right),gamma(0)=gamma_{0} (9).
We use the cost function (20) E m = [ (T R p - 1 ) ∕ 0. 1 ] 2, if R p oscillates, ∞, otherwise, where T R p is the period of the oscillations of R p for a parameter point θ = (k1, k2,..., k12).
Similar(57)
After decompositions, we can use the cost function-searching algorithm to find the best basis set ( left{{D}_l^{ k)}right} ) among all the possible basis sets, which can represent the spatial and frequency domain information of the analyzed dataset more effectively than all other basis sets.
Specifically, we used the cost function in MARXAN to include the ecological value of marine habitats while identifying spatial solutions for terrestrial nesting habitat reserves.
All predictions are evaluated by using the cost function g1.
All predictions are evaluated using the cost function g2.
The optimal sequence can be found by using a computer search using the cost function (31).
The strategy P knn is used with k=3 neighbors, and thresholds β j are fixed using the cost function TP_cost.
Back propagation: Adjust the parameters w p, q, W p a n d b p using the cost function (8).
4) All predictions are evaluated by using the cost function g1. 5) The optimal switching state that corresponds to the optimal voltage vector that minimizes the cost function is selected to be applied at the next sampling time. .
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com