期刊文献+

蚁群算法可视化软件的设计和实现 预览

Design and implementation of ant colony algorithm visualization software
在线阅读 下载PDF
分享 导出
摘要 目前的蚁群算法一般都以数值形式展示结果,而蚁群自适应、自组织的行为过程完全被掩盖。对研究者和学习者来说,蚁群行为过程的透明性极易导致理解上的困难和偏差。针对这一问题,文章基于经典蚁群算法,采用现代化可视化方法和技术,设计和实现了面向多种策略的蚁群算法可视化软件。 The current ant colony algorithm usually presents the results in numerical form,but the adaptive capacity and self-organizing behavior process of ant colony is completely covered up.For researchers and learners,the transparency of the behavior process of ant colony can easily lead to difficulties and deviations in understanding.Aiming at this problem,based on the classical ant colony algorithm and modern visualization method,the visualization software of ant colony algorithm is designed and implemented.
作者 陈嘉圣 李泓波 罗正德 李泽钦 彭攀宇 黄梓琛 Chen Jiasheng;Li Hongbo;Luo Zhengde;Li Zeqin;Peng Panyu;Huang Zichen(School of Computer and Software,Zhaoqing University,Zhaoqing 526061,China)
出处 《无线互联科技》 2019年第10期33-34,共2页
基金 大学生创新创业训练计划项目(国家级) 项目编号:No.201710580018。
关键词 蚁群算法 可视化 人工智能 ant colony algorithm visualization artificial intelligence
作者简介 陈嘉圣(1994-),男,广东惠州人,本科生;研究方向:群体智能;通信作者:李泓波(1971-),男,黑龙江大庆人,副教授,博士;研究方向:群体智能,数据挖掘,社交网络.
  • 相关文献

参考文献1

二级参考文献22

  • 1Nie CH. Concepts and Methods of Software Testing. Beijing: Tsinghua University Press, 2013.1-22 (in Chinese). 被引量:1
  • 2Nie CH. Combinatorial Testing. Beijing: Beijing Science Press, 2015.1-119 (in Chinese). 被引量:1
  • 3McCaffrey JD. Generation of pairwise test sets using a genetic algorithm. In: Proc. of the Int'l Conf. on Computer Software and Applications (COMPSAC). 2009.626-631. [doi: 10.1109/COMPSAC.2009.91 ]. 被引量:1
  • 4Nie CH, Leung H. A survey of combinatorial testing. ACM Computing Surveys (CSUR), 2011,43(2):11. [doi: 10.1145/1883612. 1883618]. 被引量:1
  • 5Yu L, Tai KC. In-Parameter-Order: A test generation strategy for pairwise testing. In: Proc. of the High-Assurance Systems Engineering Symp. 1998.254-261. [doi: 10.1109/HASE. 1998.731623 ]. 被引量:1
  • 6Bryce RC, Colbourn CJ. The density algorithm for pairwise interaction testing. SoftwareTesting, Verification and Reliability, 2007,17(3):159-182. [doi: 10.1002/stvr.365]. 被引量:1
  • 7Dorigo M, Maniezzo V, Colorni A. Ant system: Optimization by a colony of cooperating agents. IEEE Trans. on Systems, Man, and Cybernetics (Part B Cybernetics), 1996,26(1):29-41. [doi: 10.1109/3477.484436]. 被引量:1
  • 8Dorigo M, Stutzle T. Ant Colony Optimization. Cambridge: MIT Press, 2004. 1-151. 被引量:1
  • 9Shiba T, Tsuchiya T, Kikuno T. Using artificial life techniques to generate test cases for combinatorial testing. In: Proc. of the Computer Software and Applications Conf. 2004.72-77. [doi: 10.1109/CMPSAC.2004.1342808]. 被引量:1
  • 10Chen X, Gu Q, Li A, Chen DX. Variable strength interaction testing with an ant colony system approach. In: Proc. of the Asia-Pacific Software Engineering Conf. (ASPEC). 2009.160-167. [doi: 10.1109/APSEC.2009.18]. 被引量:1

共引文献10

投稿分析

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部 意见反馈