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Genotic algorithm optimization method and network

机译:遗传算法优化方法及网络

摘要

Sensors are selected from a sensor network for tracking of at least one target. The sensors are selected using a genetic algorithm construct having n chromosomes, wherein each chromosome represents one sensor, defining a fitness function based on desired attributes of the tracking, selecting one or more of the individuals for inclusion in an initial population, executing a genetic algorithm on the initial population until defined convergence criteria are met, wherein execution of the genetic algorithm has the steps of choosing the fittest individual from the population, choosing random individuals from the population and creating offspring from the fittest and randomly chosen individuals. In one embodiment, only i chromosomes are mutated during any one mutation, wherein i has a value of from 2 to n−1.
机译:从传感器网络中选择传感器,以跟踪至少一个目标。使用具有n个染色体的遗传算法构建体选择传感器,其中每个染色体代表一个传感器,根据跟踪的所需属性定义适应度函数,选择一个或多个个体以包括在初始种群中,执行遗传算法在初始种群上,直到满足定义的收敛标准为止,其中遗传算法的执行具有以下步骤:从种群中选择最适合的个体;从种群中选择随机的个体;以及从适度和随机选择的个体中产生后代。在一个实施方案中,在任何一个突变过程中仅i个染色体被突变,其中i的值为2至n-1。

著录项

  • 公开/公告号US6957200B2

    专利类型

  • 公开/公告日2005-10-18

    原文格式PDF

  • 申请/专利权人 ANNA L. BUCZAK;HENRY WANG;

    申请/专利号US20010893108

  • 发明设计人 HENRY WANG;ANNA L. BUCZAK;

    申请日2001-06-27

  • 分类号G06F15/18;

  • 国家 US

  • 入库时间 2022-08-21 22:20:49

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