离散Hopfield神经网络在职业院校学生综合素养评价中的应用研究  

作　　者：俞骋 

机构地区：[1]宁波市教育科学研究所,浙江宁波315100

出　　处：《科技创新与应用》2024年第20期150-153,共4页Technology Innovation and Application

摘　　要：为克服教育评估中人为因素的干扰,提高评估的准确性和效率,该文探索将离散Hopfield神经网络应用到职业院校学生综合素养的评价中。Matlab仿真发现,通过设置合适的神经元平衡点,离散Hopfield神经网络可根据输入的指标数据对学生的职业综合素养给出有效的评估,评估结果与专家评估的结果完全一致。In order to overcome the interference of human factors in educational evaluation and improve the accuracy and efficiency of educational evaluation,this paper explores the application of Discrete Hopfield Neutral Network(DHNN)to the evaluation of vocational college students'comprehensive literacy.Matlab simulation shows that by setting appropriate neuron balance point,the Discrete Hopfield Neutral Network can effectively evaluate students'professional comprehensive literacy according to the input index data,and the evaluation results are completely consistent with the results of expert evaluation.

关 键 词：离散HOPFIELD神经网络 职业院校 综合素养评价 二值化编码 教育评估 

分 类 号：G434[文化科学—教育学]