Sentence examples for data can be formulated from inspiring English sources

Hence, the estimation of high-dimensional subsurface flow properties from dynamic performance and monitoring data can be formulated and solved as a sparse reconstruction inverse problem.

The task of finding such a plane for a given kernel function with the constraint of maximizing the distance of the plane to the training data can be formulated as a convex optimization problem and computed efficiently [29], [30], [31].

Therefore, the question of PWM motif discovery from ranked experimental data can be formulated as quantifying the mutual enrichment level for the two ranked lists L1 and L2.

Several illustrative examples are available demonstrating different features of the toolbox and how qualitative information and quantitative data can be formulated.

The size of a sample may be pragmatically determined by financial constraints, staff time for recruitment and by sample size calculations where a specific improvement goal from previous patient experience data can be formulated.

With a backcross design, the QTL has two possible genotypes (as do the markers) which shall be indexed by k = 1, 2. The likelihood function based on the phenotype and marker data can be formulated as (4) L = ∏ i = 1 n [ ∑ k = 1 2 p k | i f k (y i | Ω ) ] where p k | i is the conditional probability of a QTL genotype given the genotype of a marker interval for progeny i.

Since the clustering problem on numeric data sets can be formulated as a typical combinatorial optimization problem, many researches have addressed the design of heuristic algorithms for finding sub-optimal solutions in a reasonable period of time.

Then the time delay reward of the ith SU source in data transmission can be formulated as: begin{aligned}&R_{D,i} = frac{{T - tau_{i} }}{T} &{text{subject to}}:;Eleft( {tau_{i} } right)left( {1 + sigma_{{tau_{i} }} } right) le T end{aligned} (21 where (Eleft( {tau_{i} } right)) and (sigma_{{tau_{i} }}) is the mean and the variance of (tau_{i}), respectively.

Since most machine learning algorithms can be used to find an approximate solution for the optimization problem, they can be employed for most data analysis problems if the data analysis problems can be formulated as an optimization problem.

In terms of mathematic form, the mean data access time can be formulated as follows: Lemma 3 Suppose that the server database contains N data items D 1, D 2, …, D N for broadcasting.

Then the inverse problem with the measured output data f ( t ) can be formulated as the following operator equation: Φ [ p, q ] = f, ( p ( t ), q ) ∈ P, f ∈ H 0, 2 [ 0, T ]. (4).