Sentence examples for applying fitness from inspiring English sources

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This paper provides an introduction to the concept of developing and applying fitness landscape theory to help manufacturing managers make decisions in such a manner.

Basanta et al (2008) have described the interplay of proliferative and motile phenotypes in a developing tumour using game theory, applying fitness cost tradeoffs between the two phenotypes.

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In an age of scientifically applied fitness, superior nutrition and stifling tactics they have disinterred some of the glories we had reason to believe had been buried for ever with the passing of wonderfully creative teams like Hungary, Brazil and, yes, Holland.

Proper designing of the applied fitness measure plays an essential role in the feature synthesis process.

After computing the fitness score of each particle position with the applied fitness function, the following update equations are used for the personal best position and dimension of particle p for iteration t + 1: y p d p t + 1 t + 1 = { y p d p t + 1 t, if F x p d p t + 1 t + 1 > F y p d p t + 1 t x p d p t + 1 t + 1, else, (1).

The resulting phenotypes are then assessed by applying the fitness function to each one of them.

Since each individual represents a similarity function, applying this fitness function corresponds to ranking the set of training documents according to the set of training queries, using the similarity function defined by one individual.

By applying different fitness functions to the model in separate evolutionary sessions, different synaptic plasticity rules could be evolved by the system: Hebbian- like LTP plasticity, Anti-Hebbian-like Anti-Hebbian-like Anti-Hebbian-like LTDd plasticityptic plasticity and Hebbian- like STDP.

Three objectives, the size, homogeneity and row variance of biclusters, are satisfied simultaneously by applying three fitness function in optimization framework.

Applying a fitness function that varied over time while retaining certain invariant features in the adaptive landscape (e.g. persistently favoring bilateral symmetry) successfully selected for enhanced evolvability (Reisinger and Miikkulainen 2006).

As described in Fig.  6, the input dataset contains the training set that is fed to the GA in order to select the best features that discriminate between HVs and MDD patients, and by applying the fitness function (explained in Feature selection).

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