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Normal parameter reduction in soft set based on particle swarm optimization algorithm

机译：基于粒子群算法的软集合法线参数约简

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摘要

Parameter reduction in soft set is a combinatorial problem. In the past, the problem of normal parameter reduction in soft set is usually be solved by deleting dispensable parameters, that is, by the trial and error method to search the dispensable parameters. This manual method usually need much time to reduce unnecessary parameters, and the method is more suitable for small data. For the large data, however, it is impossible for people to reduce parameters in soft set. In this paper, the particle swarm optimization is applied to reduce parameters in soft set. Firstly, a definition is introduced to define the dispensable core, and some cases about the dispensable core are discussed. Then the normal parameter reduction model is built and the particle swarm optimization algorithm is employed to reduce the parameters. Experiments have shown that the method is feasible and fast.
机译：软集合中的参数减少是一个组合问题。过去，通常通过删除可有可无的参数来解决软集合中正常参数减少的问题，即通过反复试验法来搜索可有可无的参数。这种手动方法通常需要大量时间来减少不必要的参数，并且该方法更适合于小数据。但是，对于大数据，人们无法减少软集合中的参数。本文应用粒子群算法对软集合中的参数进行约简。首先，介绍了一种定义可分配核心的定义，并讨论了有关可分配核心的一些情况。然后建立正常参数约简模型，并采用粒子群优化算法对参数进行约简。实验表明，该方法可行，快速。

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  • 来源
    《Applied Mathematical Modelling》 |2015年第16期|4808-4820|共13页
  • 作者

    Zhi Kong; Wenhua Jia; Guodong Zhang; Lifu Wang;

  • 作者单位

    School of Control and Engineering, Northeastern University At Qinhuangdao, Hebei, Qinhuangdao 066004, China;

    School of Control and Engineering, Northeastern University At Qinhuangdao, Hebei, Qinhuangdao 066004, China;

    School of Control and Engineering, Northeastern University At Qinhuangdao, Hebei, Qinhuangdao 066004, China;

    School of Control and Engineering, Northeastern University At Qinhuangdao, Hebei, Qinhuangdao 066004, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Normal parameter reduction; Soft set; Particle swarm optimization; Reduction;

    机译：正常参数缩减;软套装;粒子群优化;减少;

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