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The constant crossover CR practically controls the diversity of the population [44].
The constant crossover (CR) reflects the probability with which the trial individual inherits the actual individual's genes, i.e., which and how many components are mutated in each element of the current population [17, 43].
The distance for each 1 Mb window was calculated based on SNP positions according to the Affymetrix data, assuming a constant crossover rate between two adjacent SNP markers.
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The EI criterion and the Kriging-HDMR are used to adjust scale factor F and crossover constant Cr, respectively.
The key parameters of control in DE are population size (NP), scaling factor (F) and crossover constant (C R ).
Table 1 DE control parameters Number of dimensions D 4 Population size NP 20 Mutation constant F 0.5 Crossover constant CR 0.9 parameters; boundaries V j (U) 12 (j = 1, …, 4) V j (L) −12.
The key features of DE are three control parameters, that is, the population size NP, crossover constant CR, and scaling factor Sf.
Here, the population size, scaling factor (F), crossover constant (C R ) and maximum iteration number have been selected 100, 1, 1 and 300 respectively for this case.
The crossover constant (C R ), in the range 0 ≤ C R ≤ 1, controls the diversity of the population and aids the algorithm to escape from local optima.
Here, the population size, scaling factor (F), crossover constant (C R ) and maximum iteration number have been selected 10, 0.3, 1.0 and 50 respectively.
end{aligned} (3)Here, (r) is a randomly chosen integer from the interval [1, (n)]; Cr is a user-defined crossover constant from [0, 1].
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