基于卷积神经网络的高职产教融合评价算法研究  

Research on Evaluation Algorithm of Production-Education Integration in Higher Vocational Colleges based on Convolutional Neural Network

作　　者：杨斐[1] 石磊[2] YANG Fei;SHI Lei(College of Engineering Science and technology,Fuyang Institute of Technology,Fuyang 236031,Anhui Province,China;Youth League Committee,Fuyang Institute of Technology,Fuyang 236031,Anhui Province,China)

机构地区：[1]阜阳职业技术学院工程科技学院,安徽阜阳236031 [2]阜阳职业技术学院团委,安徽阜阳236031

出　　处：《景德镇学院学报》2022年第6期129-132,共4页Journal of JingDeZhen University

基　　金：安徽高校自然科学研究项目(KJ2021ZD0154);安徽省教育厅高水平专业群(高职)(2020zyq63)。

摘　　要：本文通过对卷积神经网络的高职产教融合评价算法进行两轮筛选,选出功能相对独立且具有代表性的评价指标,构建评价指标体系。利用改进层次分析法(Analytic Hierarchy Process,AHP)计算每个评价指标的权重;利用卷积神经网络得出高职产教融合评价分值,确定产教融合效果等级。Through two rounds of screening for the evaluation algorithm of higher vocational production-education integration based on convolutional neural network,this paper selects the relatively independent and representative evaluation indicators and constructs the evaluation indicator system.The weight of each evaluation index is calculated by using the improved analytic hierarchy process(AHP);and the effect grade of the production-education integration is determined by using convolution neural network to obtain the evaluation score of the production-education integration in higher vocational education.

关 键 词：卷积神经网络 高职院校 产教融合 指标选取 权重计算 

分 类 号：G71[文化科学—职业技术教育学]