Sentence examples for mutation probabilities are from inspiring English sources

Crossover and mutation probabilities are 80 and 10%, respectively.

Adaptive genetic algorithm (AGA), in which crossover and mutation probabilities are dynamically adjusted according to the population fitness through generations, outperformed simple GA (SGA).

To allow the algorithm to jump out of local optima, the adaptive mutation probabilities are presented and the stem-loop mutation operator is adopted with the other mutation operators.

The adaptive genetic algorithm (AGA) is an improved form of simple genetic algorithm in the sense that the crossover and mutation probabilities are no longer kept fixed at pre-assigned values but adjusted by the algorithm at each generation according to the fitness function response of the solution (chromosome).

For κ>1, the mutation probabilities are not equal.

For GAFCMdd and VGAFC, the crossover and mutation probabilities are taken to be 0.8 and 0.3, respectively.

However, the crossover and mutation probabilities were updated in every generation.

The results show that the parameters with significant (95% confidence) effect are initial population, the population size and the jump and creep mutation probabilities, being the ones in which alterations should be made during a GA study of optimisation, in the search for the optimum.

For both mutation probability functions, we examined three different coefficients such that the maximum mutation probabilities were 0.01, 0.05, and 0.1, respectively.

Large differences in mutation probabilities were observed by combining ER status and other informative markers with family history.

HCV sequence-derived mutation probabilities were used to estimate the extent of base composition variations for CoV species.