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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Neutral offspring controlling operators in genetic programming
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Neutral offspring controlling operators in genetic programming

机译:基因编程中的中性后代控制算子

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摘要

Code bloat, one of the main issues of genetic programming (GP), slows down the search process, destroys program structures, and exhausts computer resources. To deal with these issues, two kinds of neutral offspring controlling operators are proposed-non-neutral offspring (NNO) operators and non-larger neutral offspring (NLNO) operators. Two GP benchmark problems-symbolic regression and 11-multiplexer-are used to test the new operators. Experimental results indicate that NLNO is able to confine code bloat significantly and improve performance simultaneously, which NNO cannot do. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
机译:代码膨胀是基因编程(GP)的主要问题之一,它减慢了搜索过程,破坏了程序结构并耗尽了计算机资源。为了解决这些问题,提出了两种中性后代控制算子:非中性后代(NNO)算子和非较大中性后代(NLNO)算子。两个GP基准测试问题-符号回归和11-多路复用器-用于测试新的运算符。实验结果表明,NLNO能够显着地限制代码膨胀并同时提高性能,而NNO无法做到。 (c)2006模式识别学会。由Elsevier Ltd.出版。保留所有权利。

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