[1]刘芳瑞,陈宏伟. 基于改进樽海鞘群算法的垃圾邮件分类[J].湖北工业大学学报,2021,(1):61-64.
　LIU Fangrui,CHEN Hongwei. An Improved Salp Swarm Algorithm for Spam Classification[J].,2021,(1):61-64.
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 基于改进樽海鞘群算法的垃圾邮件分类()
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《湖北工业大学学报》[ISSN:1003-4684/CN:42-1752/Z]

卷:
期数:
2021年第1期
页码:
61-64
栏目:
湖北工业大学学报
出版日期:
2021-02-18

文章信息/Info

Title:
 An Improved Salp Swarm Algorithm for Spam Classification
文章编号:
1003-4684(2021)01-0061-04
作者:
 刘芳瑞;  陈宏伟
 湖北工业大学计算机学院， 湖北 武汉 430068
Author(s):
 LIU Fangrui; CHEN Hongwei
 School of Computer Science, Hubei Univ. of Tech., Wuhan 430068,China
关键词:
 ; 樽海鞘群算法;  混沌映射;  惯性策略;  垃圾邮件
Keywords:
 ; salp swarm algorithm;  chaos mapping;  inertial strategy;  spam
分类号:
TP399
文献标志码:
A
摘要:
 为了规避电子邮件中的垃圾信息，提出一种基于改进樽海鞘群算法的垃圾邮件分类。因樽海鞘群算法缺少惯性参数和找到全局搜索潜在解决方案的能力，故利用Tent映射对初始种群施加混沌扰动，并在位置更新中加入了惯性权重策略。采用增强的算法优化分类器的参数，使得分类效果愈加显著。基于不同分类器和算法的实验表明，优化后的算法明显提高了垃圾邮件的分类精确度和最佳识别准确度。
Abstract:
 In order to avoid spam in E-mail, an improved salp swarm algorithm for spam classification is proposed. However, the SSA lacks inertial parameters and ability to find global search potential solutions. The chaotic perturbation is applied to the initial population using Tent mapping, and the inertial weight strategy is added to the position update. Then, the parameters of the classifier are optimized by the enhanced algorithm, which makes the classification effect more significant. Finally, based on different classifiers and algorithm, experiments demonstrate that the optimized algorithm has an enormously increase on classification accuracy and the optimal recognition precision of spam.

参考文献/References:

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备注/Memo

备注/Memo:
［收稿日期］ 2020-07-20
［基金项目］ 国家自然科学基金项目（61772180）
［第一作者］ 刘芳瑞(1996-)，女，河南许昌人，湖北工业大学硕士研究生，研究方向为大数据
［通信作者］ 陈宏伟(1975-)，男，湖北武汉人，工学博士，湖北工业大学教授，研究方向为大数据
更新日期/Last Update: 2021-02-19