Sentence examples for branch optimization from inspiring English sources
For example, branch optimization can introduce new conditional branches.
In other words, at each branch, optimization over a three-dimensional space is required to obtain the unknown parameters.
Also, educating developers with energy efficient application development techniques including loop unrolling, branch optimization, dead store elimination, value numbering, code inlining, constant propagation, code motion, inter-procedural analysis, and instruction scheduling, greens smartphone operations [33].
The reference tree topologies used here as the most probable one are Tree-6 of [ 34] for mammalian-mtProt, the one reported in [ 35] for cpProt-55, and the one inferred by the FastTree version 2 [ 36] for HA_Human-Flu-A-H1N1. Branch optimization of phylogenetic trees and their maximum log-likelihood values are calculated using Phyml [ 37] modified for the mechanistic codon substitution model.
We use the FMutSel0 model in the program CODEML [PAML package (Yang 2007; Yang and Nielsen 2008)], using the branch-by-branch optimization option and empirical codon frequencies (method = 1 and estFreq = 0 in the CODEML control file).
3) A particularly interesting branch of optimization research focuses on the expansion from single-objective to multi-objective optimization.
Thus, for an M-generator B-bus power system with L branches, the optimization objective for optimizing the controlled islanding schemes can be represented by hbox{min},O = sumlimits_{l = 1}^{L} {left| {(1 - a_{l} )F_{l}^{text{P}} } right|} (14 where (F_{l}^{text{P} }) is the actual active power of transmission line l before islanding; a l is the operating state of transmission line l.
Using new methodologies and computer power, they made significant progress in a branch of optimization that George believed is "where the real problems are". In 1996, George's teaching activity came to a close, but his labors continued.
The study of equilibrium problems is an important branch of optimization theory and nonlinear functional analysis.
For example, if we analyze 40 randomly selected 16S rRNAs with FastTree and the GTR+CAT model, and we increase the rounds of branch length optimization to 4 (-mlacc 4), then the average improvement for any NNI is just 1.1 log-likelihood units in the second round of branch length optimization and just 0.04 in rounds 3 and 4 combined.
However, GMYC analysis is currently computationally more difficult to implement, especially because it requires a detour via branch length optimization and computation of an ultrametric tree and algorithms, which are prone to error if branch lengths are zero.
