Segment-preserving crossover in genetic algorithms

Data processing: artificial intelligence – Machine learning – Genetic algorithm and genetic programming system

Reexamination Certificate

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Reexamination Certificate

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08005772

ABSTRACT:
Cross over (S560) in a genetic algorithm (128) is adapted for deriving an optimal mask (S540), or set of segments of a line. Each mask of a chromosome is subject to cross over with the respective mask of the other parent. Any overlapping part, whether a filtering (320) or pass-through part (350), is retained in the child (334) to preserve commonality. The part is preferably, potentially extended, according to one parent or the other, as decided pseudo-randomly (430). In a preferred application, spectrums of candidate blood constituents are masked for fitting to ensemble spectrums of test blood samples (S610, S620). The developed masks are applicable to constituent spectrums to create masked spectrums (S710) which are then applicable to an actual blood sample to be analyzed (S720).

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