Sentence examples for genetic differential from inspiring English sources
Seven optimization algorithms, least-squares, Nelder Mead, genetic, differential evolution, hybrid learning, particle swarm, and simulated annealing are used to determine optimally the design parameters of the ANFIS.
For two days now, Og had wandered aimlessly from one sparsely attended colloquium to another, trying to make sense of such weirdly punctuated panel topics as "De[con]struc(t)ing Australopithecus" and "The Urge Toward Biodiversity: Primitive (Wo Man's Genetic Differential Component".
The two species' divergence is relatively recent, during the time of the last ice age, therefore the genetic differential between them (and also the difference in their appearance) is relatively small.
These findings provide evidence for the interactive effects of genes and environment (in this study, children born at higher risk) on parenting, and are consistent with a genetic differential susceptibility model of parenting by demonstrating that some parents are inherently more susceptible to environmental influences, both good and bad, than are others.
We also included studies that addressed genetic differential susceptibility rather than genetic risk (i.e., "for better and for worse" interactions; Belsky 2005).
In principle, this process could be automated, with ascertainment of clinical features from the electronic medical record, derivation of a comprehensive genetic differential diagnosis, and orthogonal analysis of filtered genomic variants.
Asher's 'causes', - the laws of physics, mutation and genetic variation, differential reproduction, differential mortality, and the like - are the stuff of science, which can be studied without reference to the direct interposition of God.
These concepts included genetic variation, differential survival, differential reproduction, and correct use of the term "fitness" in two different contexts.
The design procedure and the optimization are performed with a genetic algorithm differential evolution — DE.
EP algorithms are different from other evolutionary algorithms (genetic algorithm, differential evolution and genetic programming) because it does not require crossover operation.
The metaheuristics selected are: generational and a steady-state Genetic Algorithm, Differential Evolution, and Particle Swarm Optimization.
