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Statements

Subject Item: dbr:Defining_length
dbo:wikiPageWikiLink: dbr:Crossover_(genetic_algorithm)

Subject Item: dbr:Inheritance_(genetic_algorithm)
dbo:wikiPageWikiLink: dbr:Crossover_(genetic_algorithm)

Subject Item: dbr:Genetic_operator
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Subject Item: dbr:Omega
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Subject Item: dbr:Gene_expression_programming
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Subject Item: dbr:Convergence_(evolutionary_computing)
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Subject Item: dbr:Crossover_(genetic_algorithm)
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rdfs:label: Creuament (algorisme genètic) Recombinação (computação evolutiva) Crossover (genetic algorithm) Recombinación (computación evolutiva) Rekombination (evolutionärer Algorithmus) Кросинговер (генетичний алгоритм) 交叉 (遗传算法)
rdfs:comment: In genetic algorithms and evolutionary computation, crossover, also called recombination, is a genetic operator used to combine the genetic information of two parents to generate new offspring. It is one way to stochastically generate new solutions from an existing population, and is analogous to the crossover that happens during sexual reproduction in biology. Solutions can also be generated by cloning an existing solution, which is analogous to asexual reproduction. Newly generated solutions are typically mutated before being added to the population. Кросинговер - це один із видів оператора рекомбінації генетичного алгоритму. Застосовується на хромосомах з бінарними генами. В літературі зустрічаються ще такі варіанти назви оператора рекомбінації: кроссовер або схрещування. La recombinación (en inglés, crossover) es un operador genético utilizado en los algoritmos genéticos para generar variación en la programación de un cromosoma o cromosomas de una generación a la siguiente. Es análogo a la recombinación de la reproducción sexual biológica, en la que los algoritmos genéticos se inspiran. Als Rekombination oder Crossover wird bei evolutionären Algorithmen die Erzeugung eines neuen Genoms (auch als Filialgenom bezeichnet) aus (in der Regel) zwei Elterngenomen (Parentalgenomen) bezeichnet. Eine Funktion, die eine zulässige Menge von Parentalgenomen auf eine Menge von Filialgenomen abbildet, heißt Rekombinationsfunktion. Eine Rekombinationsfunktion ist ein genetischer Operator. In der Literatur ist neben der Rekombination auch häufig von Crossover die Rede und beide Begriffe werden meist synonym verwendet. 交叉（crossover）是遗传算法中由遗传学中染色体交叉互换、生物杂交等现象发展来的一个算法。在自然环境中，基因重组对生物的进化起到非常关键的作用，同理，杂交操作也是遗传算法的核心部分。 Parlant d'algorismes genètics, el creuament és un operador genètic utilitzat per variar la programació d'un cromosoma o cromosomes d'una generació a la següent. És anàleg a la reproducció biològica, en la que els algorismes genètics es basen. Em algoritmos genéticos a recombinação ou crossover é um operador genético usado para variar a programação de um cromossomo ou cromossomas de uma geração para a próxima. É análogo à reprodução e recombinação genética, sobre as quais os algoritmos genéticos são baseados. Uma recombinação é um processo de se pegar mais de uma solução progenitora e produzir uma solução descendente a partir deles. Existem métodos para a seleção dos cromossomos. Alguns deles são fornecidos abaixo.
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dcterms:subject: dbc:Genetic_algorithms
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dbo:abstract: Em algoritmos genéticos a recombinação ou crossover é um operador genético usado para variar a programação de um cromossomo ou cromossomas de uma geração para a próxima. É análogo à reprodução e recombinação genética, sobre as quais os algoritmos genéticos são baseados. Uma recombinação é um processo de se pegar mais de uma solução progenitora e produzir uma solução descendente a partir deles. Existem métodos para a seleção dos cromossomos. Alguns deles são fornecidos abaixo. Parlant d'algorismes genètics, el creuament és un operador genètic utilitzat per variar la programació d'un cromosoma o cromosomes d'una generació a la següent. És anàleg a la reproducció biològica, en la que els algorismes genètics es basen. La recombinación (en inglés, crossover) es un operador genético utilizado en los algoritmos genéticos para generar variación en la programación de un cromosoma o cromosomas de una generación a la siguiente. Es análogo a la recombinación de la reproducción sexual biológica, en la que los algoritmos genéticos se inspiran. 交叉（crossover）是遗传算法中由遗传学中染色体交叉互换、生物杂交等现象发展来的一个算法。在自然环境中，基因重组对生物的进化起到非常关键的作用，同理，杂交操作也是遗传算法的核心部分。 Als Rekombination oder Crossover wird bei evolutionären Algorithmen die Erzeugung eines neuen Genoms (auch als Filialgenom bezeichnet) aus (in der Regel) zwei Elterngenomen (Parentalgenomen) bezeichnet. Eine Funktion, die eine zulässige Menge von Parentalgenomen auf eine Menge von Filialgenomen abbildet, heißt Rekombinationsfunktion. Eine Rekombinationsfunktion ist ein genetischer Operator. In der Literatur ist neben der Rekombination auch häufig von Crossover die Rede und beide Begriffe werden meist synonym verwendet. Ziel der Rekombination ist es, gute Eigenschaften zweier verschiedener Eltern auf ein Kind zu übertragen. Im Vergleich zu Algorithmen, die nur die Mutation zur Veränderung der Genome benutzen, können so möglicherweise schneller Individuen gefunden werden, die zwei gute Eigenschaften A und B in sich tragen, wenn es vorher nur Individuen gab, die entweder nur über A oder B verfügten. Generell gilt, dass die Erzeugung von Elternklonen aus Effizienzgründen zu vermeiden ist. Gute Rekombinationsfunktionen zeichnen sich dadurch aus, dass sie zumindest die guten Eigenschaften der Eltern erhalten und nicht so rekombinieren, dass diese Eigenschaften zerstört werden. Für verschiedene Genom- und Problemtypen eignen sich verschiedene Rekombinationstypen unterschiedlich gut: Кросинговер - це один із видів оператора рекомбінації генетичного алгоритму. Застосовується на хромосомах з бінарними генами. В літературі зустрічаються ще такі варіанти назви оператора рекомбінації: кроссовер або схрещування. In genetic algorithms and evolutionary computation, crossover, also called recombination, is a genetic operator used to combine the genetic information of two parents to generate new offspring. It is one way to stochastically generate new solutions from an existing population, and is analogous to the crossover that happens during sexual reproduction in biology. Solutions can also be generated by cloning an existing solution, which is analogous to asexual reproduction. Newly generated solutions are typically mutated before being added to the population. Different algorithms in evolutionary computation may use different data structures to store genetic information, and each genetic representation can be recombined with different crossover operators. Typical data structures that can be recombined with crossover are bit arrays, vectors of real numbers, or trees.
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Subject Item: dbr:Learning_classifier_system
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Subject Item: dbr:Chromosome_(genetic_algorithm)
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Subject Item: dbr:Fly_algorithm
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Subject Item: dbr:Recombination
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Subject Item: dbr:Java_Evolutionary_Computation_Toolkit
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Subject Item: dbr:Hyperparameter_optimization
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Subject Item: dbr:Edge_recombination_operator
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Subject Item: dbr:Effective_fitness
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Subject Item: dbr:Sperm_Chromatin_Structure_Assay
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Subject Item: wikipedia-en:Crossover_(genetic_algorithm)
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