###
DOI:
计算机系统应用英文版:2015,24(2):75-81
本文二维码信息
码上扫一扫!
基于人工智能的高职院校专业办学水平评估系统
(重庆工业职业技术学院 机械工程学院, 重庆 401120)
Realization System of Higher Vocational College's Specialty Education Level Assessment Based on Artificial Intelligence
(Mechanic Engineering College, Chongqing Industry Polytechnic College, Chongqing 401120, China)
摘要
图/表
参考文献
相似文献
本文已被:浏览 1248次   下载 2676
Received:June 10, 2014    Revised:June 30, 2014
中文摘要: 以重庆工职院机械学院的国家示范建设重点专业“数控技术”为研究目标, 给出了一个完善的校内自我评估模式, 建立了相关的指标体系和质量标准. 运用模糊神经网络的原理和方法, 建立了基于FNN-ES的综合评价模型和基于VC++的评估软件具体实现, 给出了使用人工评估的结果对智能模型进行训练和使用的详细过程. 利用matlab验证和改善该FNN算法的性能, 训练成熟的软件可用于校内成熟专业的评估,并进而推广到其它院校, 理论和实践的结果表明, FNN-ES用于专业评估能克服各种人为因素, 使评估结果更科学、稳定和合理, 能为省级和国家级层面上的校外评估提供导向和基础数据.
Abstract:Taking the state demonstration construct key specialty "numerical control technique" of Chongqing Industry Polytechnic College as research target, this paper proposes a perfect model of self evaluation on campus. We also establish related index system and quality standards. By using the principle and method of fuzzy neural network, this paper establishes a comprehensive evaluation model based on FNN-ES, and gives a concrete Implementation of evaluation software based on VC++. This paper also presents a detailed process of employing manual evaluation's results on intelligent model's training and using. It uses matlab to validate and improve the performance of the FNN algorithm. The mature-trained intelligent system can be used for specialty assessment of mature specialty. Then it was spreaded to other colleges. The results of theory and practice researching show that FNN-ES for specialty assessment can overcome various human factors. It makes the assessment result more scientific, stable and reasonable. This system can provide guidance and basic data for off-campus specilty evalution of provincial and national level.
文章编号:     中图分类号:    文献标志码:
基金项目:
引用文本:
张新亮,钟富平.基于人工智能的高职院校专业办学水平评估系统.计算机系统应用,2015,24(2):75-81
ZHANG Xin-Liang,ZHONG FU-Ping.Realization System of Higher Vocational College's Specialty Education Level Assessment Based on Artificial Intelligence.COMPUTER SYSTEMS APPLICATIONS,2015,24(2):75-81