研究生教育水平评定的模糊聚类及混合模型的分析

Analysis of Fuzzy Clustering and the Mixed Model in Graduate Student Education Level Evaluation

目的利用模型把不同学科和某些特殊的特征联系起来,这些特征可以判定现行的研究生培养方案是否要进行修正.运用模糊逻辑和混合系统模拟研究生培养过程,产生的决策是教育机构对现有的研究生教育方案是否能够继续实施的一个评定.方法提供了对模糊聚类及混合模型的描述.使用这两项技术能够在研究生教育水平评定过程中对其所作出的判定提供支持.模糊聚类是基于模糊逻辑的,混合模型的对象是通过综合运用统计模式和专家系统而作出的研究生教育水平判定.结果利用模糊聚类和混合模型,开发一项比较技术的混合系统,PY顾问处理了培养水平的评定,"教学环境","以往研究生水平"等内容,并得到以下启示,利用电脑评定模型来帮助作出决策可以降低评定耗费,减少可能对教育专家的需求.此外,运用电脑决策辅助能使教育部门更加有效的管理其时间,这同样也会防止耗费的增加.结论对可以给教育部门提供更多信息的电脑决策辅助的利用可以给教育部门带来裨益.

Objective Diverse subjects are connected with special characters by model in this paper. The current project of graduate student cultivation, which is modified or not, is estimated by these characters. We can simulate the proceeding of graduate student cultivation with fuzzy logic and mixed system. The decision-making which is produced by the above method can assess graduate educational project whether contuine to carry into execution or not. Methods This paper provided the description to the fuzzy clustering and the mixed model. Using these two technologies may provide the support for the determination in the process of graduate student education level evaluation. The fuzzy clustering is based on the fuzzy logic, and the object of the mixed model is the graduate student education level determination which was gotten by statistical pattern and expert system. These models can relate the different discipline and certain special characteristics, and these characteristics may determine if the present raise plan for the graduate student need to be revised. In general, this decision-making is based on understanding of educational department for condition of graduate student and related experience which educational department had. Two models , which we established, can judge nonstandard of experience utilizing some uncertain information. Fuzzy systems have assessing functions relying on some information Mixed system （united statistical model with expert system） analyzes non-system questions in the process of graduate educational evaluation utilizing quantificational model and regular warehouse which is derived from expert logic. Results Using fuzzy clustering and mixed model, we exploiture a technical mixed system. It is PY consultants, that deal with the assess of cultivation level, teaching circumstance and used graduate level. Some revelation is received. To make use of computer assessing model work out decision-making can cut down the assess expence and reduce the demand of educational expert. In addition, educational department can use their time more effect and avoid expense to increase with computer decision-making. Conclusion The use of computer decision-making which can supply more information to educational department can bring benefit to educational department. Further research should concentrate on the modeling technical which sustain educational department to do much more new and effective estimation.