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The connection of the stucture of genetic set of rules and its convergencrs
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Additional resources for The Practical Handbook of Genetic Algorithms: Applications, Second Edition
Example text
The coding within Extend is in C. ” © 2001 by Chapman & Hall/CRC The genetic algorithm used the familiar genetic operators of selection, crossover and mutation. Chapter 6 includes a detailed discussion of the application of these operators to a model having real (non-integer) parameters. It will be sufficient here to note that: • The population size used could be chosen, but in these runs was 20. • Selection was elite (retention of the single best yet solution) plus tournament (selection of the best out of each randomly chosen pair of parents).
Some assays had been reported as zero gold content: these were in reality not zero, but below a reportable threshold. 25 g/tonne before taking logarithms. The logarithms of the assay values had their mean subtracted and were divided by the standard deviation, to give a standardized variable of zero mean, unit standard deviation and approximately normal distribution. The cross-product between any two of these values could therefore be taken as an estimate of the correlation coefficient. The cross products provide the raw material for testing Models 1, 2 and 3.
As an alternative to running the genetic algorithm, the simulation could also be used in “Systematic Projection” mode. Here, as discussed in Chapter 6, each of the parameters in turn is projected to its quadratic optimum. This procedure is repeated in sequence for all six parameters until an apparent minimum is reached. 6).