In a paper published in 2009, researchers from Iceland recounted their application of an interacting particle model to the capelin stock around Iceland, successfully predicting the spawning migration route for 2008.
22.
The quantum physicist postulates that a wave / particle model of energy and matter substructs universal cosmology and in this way quantum physicists and Omni artists are concerned with the same observable and intuited phenomenon.
23.
When \ epsilon = 0 the mean field particle model described above reduces to a simple mutation-selection genetic algorithm with fitness function " G " and mutation transition " M ".
24.
The Gladstone Dale relation requires a particle model of light because the continuous wave-front required by wave theory cannot be maintained if light encounters atoms or molecules that maintain a local electric structure with a characteristic refractivity.
25.
The Glauber detection theory differs from the Born probabilistic interpretation, in that it expresses the meaning of physical law in terms of relationships, counting signals in the detection processes, without assuming the particle model of matter.
26.
If G ( x ) = 1 is the unit function and \ epsilon = 1, the interaction between the particle vanishes and the particle model reduces to a sequence of independent copies of the Markov chain X _ n.
27.
The Glauber detection theory differs from the Born probabilistic interpretation, in that it expresses the meaning of physical law in terms of measured facts ( relationships ), counting events in the detection processes, without assuming the particle model of matter.
28.
New classes of mean field particle simulation techniques for Feynman-Kac path-integration problems includes genealogical tree based models, backward particle models, adaptive mean field particle models, island type particle models, and particle Markov chain Monte Carlo methods
29.
New classes of mean field particle simulation techniques for Feynman-Kac path-integration problems includes genealogical tree based models, backward particle models, adaptive mean field particle models, island type particle models, and particle Markov chain Monte Carlo methods
30.
New classes of mean field particle simulation techniques for Feynman-Kac path-integration problems includes genealogical tree based models, backward particle models, adaptive mean field particle models, island type particle models, and particle Markov chain Monte Carlo methods
