李艳灵, 李刚. 基于蚁群算法和粗糙集的信息融合教学评价[J]. 信阳师范学院学报(自然科学版), 2009, 22(4): 624-626.
引用本文: 李艳灵, 李刚. 基于蚁群算法和粗糙集的信息融合教学评价[J]. 信阳师范学院学报(自然科学版), 2009, 22(4): 624-626.
LI Yan-ling, LI Gang. Information Fusion Teaching Quality Evaluation Based on Ant Colony Algorithm and Rough Set[J]. Journal of Xinyang Normal University (Natural Science Edition), 2009, 22(4): 624-626.
Citation: LI Yan-ling, LI Gang. Information Fusion Teaching Quality Evaluation Based on Ant Colony Algorithm and Rough Set[J]. Journal of Xinyang Normal University (Natural Science Edition), 2009, 22(4): 624-626.

基于蚁群算法和粗糙集的信息融合教学评价

Information Fusion Teaching Quality Evaluation Based on Ant Colony Algorithm and Rough Set

  • 摘要: 单目标教学评价结果的不确定性较大,为此提出基于蚁群算法和粗糙集的信息融合教学评价方法.该方法首先利用粗糙集算法处理多项评价指标决策融合问题,在解决多项评价指标决策融合问题时采用蚁群算法对融合问题中的参数进行优化,然后对多源信息利用粗糙集方法进行融合.实验结果证明:本方法更加有效,利用本方法的评教结果更加公正、合理.

     

    Abstract: The uncertainty of single-objective teaching quality evaluation is large . So information fusion teaching quality evaluation based on ant colony algorithm and rough set is proposed. Firstly,the problem of a number of evaluation indicators for decision-making integration is dealed with using rough set algorithm. Parameters of integration are optimized using ant colony algorithm. Secondly,multi-source information is fused with the method of rough set. Experimental results show that this method is more effecti...

     

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