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Fuzzy Comprehensive Model of Quantitative Evaluation of College Student Party Members' Evaluation Indexes

机译:高校学生党员评价指标的模糊综合评判模型。

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With the rapid development of education, the number of college student party members has risen due to the expansion of university enrollment. However, the quality curve of college student party members is declining. They have a series of problems in their personal motivation and leading role. Constructing the evaluation indexes and quantitative assessment system for college students are not only the inevitable requirement for the Party Central Committee to improve the quality of party members, but also the necessary means to establish and improve the quality and quantity system for college students. This paper sets the five aspects of the political quality, daily performance, learning ability, work ability and innovation ability of college student party members as the first-level evaluation indexes, and adopts five principles such as the principle of directional assessment, the combination of qualitative and quantitative assessment principle, comprehensive principle, operability principle, diversity and multi-level principle. Each first-level evaluation index is refined into several secondary evaluation indexes. Through using the variation coefficient method, double weight method, parameter classification method and the like, we've given the specific steps to establish this fuzzy comprehensive model of the quantitative evaluation of college student party members' evaluation indexes so as to evaluate the overall quality of college student party members. Finally, an example is given to verify the rationality and accuracy of the proposed model.
机译:随着教育的飞速发展,由于大学入学人数的增加,大学生党员人数有所增加。但是,大学生党员的素质曲线正在下降。他们的个人动机和领导角色存在一系列问题。建立大学生评价指标和定量评价体系,不仅是党中央提高党员素质的必然要求,而且是建立和完善大学生质保体系的必要手段。本文将大学生党员的政治素质,日常工作表现,学习能力,工作能力和创新能力五个方面作为第一层次的评价指标,并采用定向评价原则,综合评价相结合的五个原则。定性和定量评估原则,综合原则,可操作性原则,多样性和多层次原则。每个第一级评估指标都会细化为几个二级评估指标。通过使用变异系数法,双重权重法,参数分类法等方法,给出了具体步骤,建立了模糊的大学生党员评价指标量化评价综合模型,从而对总体素质进行了评价。大学生党员。最后,通过实例验证了所提模型的合理性和准确性。

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