期刊文献+

蚁群聚类算法在可持续发展理念接受程度上的应用研究

Research of the Promotion Feasibility of the Idea of Sustainable Development Based on the Ant Colony Algorithm
在线阅读 下载PDF
导出
摘要 分别运用传统的LF算法和改进的蚊群聚类算法对可持续发展理念在大学生中推广的可行性进行了聚类研究。分析了影响大学生对可持续发展理念认知的六个因素,即大学生对可持续发展理念理论的掌握情况、对当今社会资源与环境问题的掌握情况、对可持续发展理念知识的需求情况、对可持续发展理念的实践情况、参与各种推广活动的积极性以及对学校各类活动的接触程度。聚类结果表明:改进的蚊群聚类算法给出了更好的聚类效果,同时可得出结论:大学生对学校开展的各类活动的接触程度成为了影响其认知的重要因素;大学生对可持续发展理念的认知情况呈现出较为明显的聚类效应,这就为可持续发展理念在大学生中的进一步推广提供了现实依据和条件,可持续发展理念在大学中的推广具有可行性。 The feasibility of the idea of sustainable development's promotion in the college students has been researched using the improved Ant Colony Algorithm and the LF.Six elements can influence the students' understanding about the idea of sustainable development: the mastery of idea,the mastery of the social's resources and environmental issues,the level of demand to the knowledge of the idea,the practice level of the idea,the activity of participating in various promotion activities and the contact level of various college activities. The results show that the improved Ant Colony Clustering Algorithm works better.The last element becomes the key influencing the understanding about this idea.The cluster result is obvious.It means that the promotion of the Idea of Sustainable Development among the students has realistic basis and condition.
出处 《中国人口·资源与环境》 CSSCI 北大核心 2011年第S2期182-185,共4页 China Population,Resources and Environment
基金 教育部人文社会科学研究项目 绿色大学建设标准与管理模式研究(编号:09YJAH063)
关键词 蚊群聚类算法 变异算子 LF算法 大学生群体 可持续发展理念 可行性 Ant Colony Clustering Algorithm mutation operator LF college students the idea of sustainable development feasibility
  • 相关文献

参考文献10

二级参考文献48

  • 1贾利民,李平,聂阿新.新一代的铁路运输系统——铁路智能运输系统[J].交通运输工程与信息学报,2003,1(1):81-86. 被引量:6
  • 2刘靖明,韩丽川,侯立文.基于粒子群的K均值聚类算法[J].系统工程理论与实践,2005,25(6):54-58. 被引量:122
  • 3黄振华 吴诚一.模式识别[M].杭州:浙江大学出版社,1991.40-62.
  • 4Kennedy J,Eberhart R C.Particle Swarm Optimization[C].In:Proc IEEE International Conference on Neural Networks,Ⅳ Piscataway,NJ:IEEE Service Center, 1995:1942~1948
  • 5Shi Y,Eberhart R C.Particle Swarm Optimization :developments,applications and resources[C].In:Proc Congress on Evolutionary Computation 2001 NJ:Piscataway,IEEE Press,2001:81~86
  • 6Shi Y,Eberhart R C.A modified particle swarm optimizer[C].In:IEEE World Congress on Computational Intelligence,1998:69~73
  • 7Shi Y,Eberhart R C.Fuzzy Adaptive Particle Swarm Optimization[C].In: Proc Congress on Evolutionary Computation, 2001:101~106
  • 8Lovbjerg M,Rasmussen T k,Krink T. Hybrid Particle Swarm Optimiser with Breeding and Subpopulation[C].In :Proc Congress on Evolutionary Computation, 2001
  • 9Ciuprina G,Ioan D,Munteanu I. Use of Intelligent-Particle Swarm Optimization in Electromagnetics[J].IEEE Trans on Magnetics ,2002;38(2): 1037~1040
  • 10Brits R,Engelbrecht AP,van den Bergh F.A Niching Panicle Swarm Optimizer[C].In:4th Asia-Pacific Conference on Simulated Evolution and Learning, 2002

共引文献471

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