Using fuzzy C-means clustering to improve fuzzy comprehensive evaluation model

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (16): 246-248.

• 工程与应用 • Previous Articles

Using fuzzy C-means clustering to improve fuzzy comprehensive evaluation model

YE Junjie，LIU Yezheng

Department of Management，Hefei University of Technology，Hefei 230009，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-06-01 Published:2011-06-01

采用模糊C均值聚类改进模糊综合评判模型

叶俊杰，刘业政

合肥工业大学管理学院，合肥 230009

Abstract

Abstract: Analyzing the fuzzy comprehensive evaluation method，this paper proposes the new evaluation model by using the FCM algorithm to improve fuzzy comprehensive evaluation method，and verifies the effectiveness of the new model by giving an example of evaluating teaching quality.The result indicates the feasibility of the model and validity of the method.

Key words: fuzzy clustering, Fuzzy C-Means（FCM） algorithm, fuzzy comprehensive evaluation method, evaluation of teaching qualities

摘要： 在对模糊综合评判法进行分析的基础上，提出使用FCM算法改进模糊综合评判法的新评价模型，并以在教师教学质量评价中的应用为例对新模型的效果进行了验证，说明了模型的可行性与方法的正确性。

关键词: 模糊聚类, 模糊C均值（FCM）算法, 模糊综合评判法, 教学质量评价

YE Junjie，LIU Yezheng. Using fuzzy C-means clustering to improve fuzzy comprehensive evaluation model[J]. Computer Engineering and Applications, 2011, 47(16): 246-248.

叶俊杰，刘业政. 采用模糊C均值聚类改进模糊综合评判模型[J]. 计算机工程与应用, 2011, 47(16): 246-248.

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Using fuzzy C-means clustering to improve fuzzy comprehensive evaluation model

采用模糊C均值聚类改进模糊综合评判模型

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