NDTPNetwork Dictionary Transfer Protocol
NDTPNelson Davis Television Productions
NDTPNon-Discriminatory Trade Policy
NDTPNational Disaster Training Program (Salvation Army)
NDTPNon-Dialable Toll Points (NANPA)
NDTPNorth Dakota Thunderstorm Project
NDTPNassau Day Training Programme
NDTPNicaragua Development Training Project
NDTPNational Department of Technology and Productivity
NDTPNorth-Bangladesh Deep Tubewell Project
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References in periodicals archive ?
Each property of proteins provides us with measurable criteria for selecting reliable NDTPs. An intuitive way is to characterize the extent of sample's violating the statistical indexes or patterns displayed in the dataset of known DTPs.
After a series of computations, a statistical result is given in Figure 6 and for the Selection Algorithm in reliable interval the threshold to screen likely NDTPs is set as l = 14 to make a trade-off between class-balance in the training dataset and reliability of NDTPs.
As we know, the dataset of the unlabeled is capable of approximating the distribution of NDTPs, but such approximation is biased because of the potential DTPs' existence.
For our problem, we denote the {[[mu].sub.0], [[sigma].sub.0]} and {[[mu].sub.1], [[sigma].sub.1]}, respectively, as the parameters for the DTPs and NDTPs distributions.
Ranking scores of the above probability in decreasing order, some reliable NDTPs are selected as the top 441 in the rankings just to maintain the same number as in Strategy 1.
In the first stage, several reliable NDTPs are screened to constitute the part of training dataset.
Considering the formulation of the general MINLP optimization problem (MINLP-G), the MINLP optimization model formulation for the NDTP is more specific, especially in terms of decision variables and constraints.
For this purpose, the set K is defined to include discrete solution alternatives k, k [member of] K(i, j), into the superstructure of the NDTP. Discrete constants [q.sub.k] in Eq.
The presented model formulation defines the balanced NDTP. The structure of the NDTP model implies that the total supply [summation over (i [member of] I)] [s.sub.i] must be equal to the total demand [summation over (j [member of] J)] [d.sub.j].
In this paper, the suitability of five different state-of-the-art MINLP optimization methods for solving the NDTP was investigated.
The MINLP optimization model formulation for the NDTP was applied to solve the test problems.
BARON and LINDOGlobal algorithms achieved the best solution for the 7 x 7 test NDTP with function D which indicates the objective function value of 480.16, see Table 10.