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The present study aims to present an improved approach for establishing a quantitative relationship between conventional well log data and sonic wave velocities (Vp, Vs and Vst as DSI log parameters) by coupling an evolutionary computational method based on a neuro-fuzzy inference system.
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As a result, in this paper, we present a botnet interaction model, obtained by coupling a fast evolutionary game dynamics to a slow population dynamics model, in which two botnet types are considered.
Six free parameters are considered in this optimization process, realized by coupling an in-house optimization library (OPAL, relying in the present case on Evolutionary Algorithms) with an industrial flow simulation code (ANSYS-Fluent).
In this work, after modeling such a question as an optimization problem, we are able to find quite interesting results by coupling a network simulator with an evolutionary algorithm.
By coupling sound evolutionary education and actively placing students in a position to "walk the walk" of our evolutionary ancestors, the students will not only reap the rewards of ancestral lifestyle changes (better physical and psychological well-being).
The present study describes a methodology for design and sizing such hybrid plants, by implementing a transient simulation model, coupled to an evolutionary optimization algorithm, allowing to address the trade off between costs and capacity factor.
In this paper we propose a novel approach called QueBN-design (Querying Bayesian network design) derived by coupling conditional probabilistic inference in Bayesian network models and evolutionary principles.
By coupling the evolution of spiders and their silk with evolutionary theory, the authors give readers a physical representation of something that is considerably unseen.
An evolutionary process is simulated to optimize a defined fitness function, and new chromosomes are obtained by coupling the chromosomes of the initial population with genetic operations (crossover and mutation).
We have designed and implemented a new strategy of evolutionary design of experiments (Evo-DoE), that efficiently explores high-dimensional spaces by coupling the power of computer and statistical modeling with experimentally measured responses in an iterative loop.
The coupling of an evolutionary analysis to a crystallographic analysis suggests that the amino acid changes are functionally significant.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com