基于RS与SVM的高校教师绩效评估模型的构建与仿真  

Construction and Simulation of Performance Evaluation Model for University Teachers Based on RS and SVM

作　　者：刘叶[1] 王帅 周庆忠 Liu Ye1, Wang Shuai2, Zhou Qingzhong2(1. Chongqing Energy College, Chongqing 402260; 2. Ground Force Service Academy, Chongqing 401311, Chin)

机构地区：[1]重庆能源职业学院,重庆402260 [2]陆军勤务学院,重庆401311

出　　处：《物流技术》2018年第7期152-156,共5页Logistics Technology

基　　金：国家社会科学基金(14CGJ014);重庆社会科学基金(2015YBGL141)

摘　　要：引入粗糙集理论,在构建高校教师绩效考评指标体系的基础上,将连续型指标数据进行离散化处理后对指标体系进行约简,从而降低模型复杂度。然后依托支持向量机的模式识别,提出高校教师绩效考评的新方法。仿真证明,所提方法精度较高,操作简单,受人为因素影响小,可以为评估高校教师绩效水平提供科学的依据。In this paper, after introducing the rough set theory and building the university teacher performance evaluation index system,we converted the continuous index data into discrete data, thus reducing the complexity of the model. Then, relying on the pattern recognition function of the support vector machine, we put forward a new method for the performance evaluation of the university teachers. The merits of the method were demonstrated at the end through a simulation experiment.

关 键 词：粗糙集 支持向量机 高校教师 绩效考评 

分 类 号：G647[文化科学—高等教育学]