It is a combinational optimization problem: given a set of items, each with a weight w i and a value v i determines the number of each item to be included in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible.
The function f i is the predictor function and a subset of the genes W i ⊆ V determining the value of the gene x i at next time step, is called the predictor set for gene x i.
The probability that the predictor f j (i ), 1 ≤ j ≤ l(i), is selected to determine the value of x i is given by (2) c j (i ) = Pr { f (i ) = f j (i ) } = ∑ l : f l i (i ) = f j (i ) Pr { f = f l }.
For each variable x i there exists a predictor set { x i 1, x i 2, …, x i k (i ) } and a Boolean predictor function (or simply predictor) f i being the i-th element of f that determines the value of x i at the next time point, i.e., (1) x i (t + 1 ) = f i (x i 1 (t ), x i 2 (t ), …, x i k (i ) (t ) ), where 1 ≤ i1 < i2 < ⋯ < i k (i ) ≤ n.
Consider the case, for instance, where I had a model to determine the value of shares in Google.
if more activities exit from vertex i (Fig. 9) we determine the value of the latest start of activities by the formula 5.
Open image in new window Fig. 8 Determination of the latest start of activities – one edge exits from vertex i {mathrm{TP}}_{mathrm{i}}={mathrm{TP}}_{mathrm{j}}hbox {mathrm{t}}_{mathrm{i}mathrm{j}} (4) if more activities exit from vertex i (Fig. 9) we determine the value of the latest start of activities by the formula 5.
This resource allocation considered in this paper contains two main challenges: (a) configuration of the ABS pattern, i.e. determines the values of ε[i] and ε ∗[i]; and (b) design of pico UE grouping, i.e., determines the values of ( {C}_{k^{{primeprime} }} ) and ( {C}_{k^{{primeprime}}}^{ast } ).
The σ i parameter is called amplitude and determines the value of the maximum distance between two inputs that the node has a prominent impact.
Transcriptomic analyses assessing factors critical for risk assessment (i.e. dose) are needed to determine the value of transcriptomic evaluation in the EST.
Otherwise, the node must determine the value of p i which corresponds to the closest approximation to preserve local k-FTN connectivity.
