计算机与数字工程Issue(11)：1981-1984,4.DOI:10.3969/j.issn.1672-9722.2015.11.018
基于最大隶属原则和权重策略的自主学习能力评价系统设计
Design of Autonomous Learning Ability Evaluation System Based on Maximum Subordination Principle and Weight Strategy
摘要
Abstract
Aiming at the problems such as too many influence factors and evaluation data in autonomous learning abili-ty ,self-evaluation model is researched and self-evaluation system is designed based on weight strategy and maximum subordi-nation principle .Firstly ,considering that excellent ,medium and poor are fuzzy concepts ,the membership functions of these three standard modes are defined .Secondly ,by analyzing main factors and sub factors ,an indictor system is built for autono-mous learning evaluation .Finally ,an autonomous learning ability self-evaluation model and a system are given .Experiment show that ,this system need not too much experts' intervention ,moreover ,it can rapidly and accurately present autonomous learning ability evaluation results according to the self-evaluation indictor information .关键词
自主学习能力/最大隶属原则/权重Key words
autonomous learning ability/maximum subordination principle/weight分类
数理科学引用本文复制引用
赵伟舟,王惠珍,张辉,景慧丽..基于最大隶属原则和权重策略的自主学习能力评价系统设计[J].计算机与数字工程,2015,(11):1981-1984,4.基金项目
全军教学改革项目数学自主学习能力评价体系研究。 （）
