Sentence examples for mutation probability in from inspiring English sources

An adaptive mutation probability in the PIRGA makes the algorithm have more chance to jump out of local optima.

Note that the mutation probability in the GA is obtained by the relationship P m  = 1 − P c.

Additional parameters that need to be specified by the user are the: 1) size of the initial population, 2) crossover probability between the pairs of the chromosome and 3) mutation probability in a parent chromosome.

By operations of extinction and immigration, the strategy of EI functions like a particular time varying mutation probability in which p m is close to 1 at the beginning of each new era and then gets smaller for the remaining generations.

To examine the interaction between male gamete mutation load and female preference based on male age, we modified our previous genetic algorithm [8] to include age-specific mutation probability in males.

The parameters of population size, generation size, random seed, and algorithm setting (e.g., mutation probability in GA and pheromone in ACO) are difficult to define to successfully find the n-loci gene gene interaction model for data sets of different sizes, i.e., sample size and SNP size.

AGA is a relatively new optimization technique which has adaptive genetic operators that dynamically update the crossover and mutation probabilities in each generation according to fitness of population to reach optimal solutions.

These mutation probabilities in turn determine κ, the total number of nonsynonymous mutations expected in the overall protein.

As mutation acquisition itself is a stochastic process, specificity in this context means that the type of genomic instability affects mutation probabilities in daughter cells of CCL and that these mutations probabilities may be estimated a priori.

The two generative models differ in how conditioning on a genome being from a cancer patient affects the ratio between the driver and passenger mutation probabilities in that genome.

The genetic algorithm parameters, such as crossover and mutation probability applied in this study are given in Table 5.