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Genetic Algorithms |
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Genetic Algorithms Models that optimize rules by mimicking the Darwinian Law of survival of the fittest. A set of rules are chosen by those that work the best. The weakest are discarded. In addition, two successful rules can be combined (the equivalent to genetic cross-overs) to produce offspring rules. The offspring can replace the parents, or they will be discarded if less successful than the parents. Mutation is also accomplished by randomly changing elements. Mutation and cross-over occur with low probability, as in nature. |
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Nature-Inspired Methods in Chemometrics: Genetic Algorithms and Artificial Neural Networks Rules may evolve in several ways that genetic algorithms use to mimic DNA evolution (e. The big thing this month is, apparently, genetic algorithms (GAs). |
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Genetic Algorithms
