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首页 > 过刊浏览>2020年第43卷第1期 >74-81. DOI:10.11835/j.issn.1000-582X.2020.01.008
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基于多目标蜂群算法的数据分类方法
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TP181

基金项目:

河南省高等学校重点科研项目（18A120005）；浙江省重点研发项目（2019C03104）。


Research of data classification method based on multi-objective artificial bee colony algorithm
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    摘要:

    为了保证运算时效的同时，提高复杂数据的分类精度，提出了基于多目标蜂群算法和极限学习机的数据分类算法。该方法以最小的特征个数和最高的分类精度为优化目标，利用改进的多目标蜂群算法对数据的特征个数和分类器参数进行寻优，针对多个有代表性的数据集进行仿真，结果表明所提出方法的有效性。

    Abstract:

    In order to improve the classification accuracy of complex data on the premise of ensuring operation efficiency, a data classification algorithm based on multi-objective artificial bee colony algorithm and extreme learning machine is proposed, it takes the number of features and the classification accuracy as the optimization objectives, and improved artificial bee colony algorithm is introduced to optimize the parameters of the classifier and the selection of features of data. The simulation results based on six data sets verify the effectiveness of the proposed method.

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王海泉,侯宇亮,魏建华,徐晓滨,苏孟豪,张姗姗.基于多目标蜂群算法的数据分类方法[J].重庆大学学报,2020,43(1):74-81.

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  • 收稿日期:2019-05-13
  • 在线发布日期: 2020-01-15
  • 出版日期: 2020-01-31
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