融入性格的E-Learning情绪模型  

Emotional model merged with personality in E-Learning

作　　者：李芮[1] 王万森[1] 

机构地区：[1]首都师范大学信息工程学院,北京100048

出　　处：《计算机工程与设计》2016年第1期216-220,共5页Computer Engineering and Design

基　　金：国家自然科学基金项目(60970052);北京市自然科学基金项目(4112014)

摘　　要：针对传统情绪模型存在缺乏性格因素的问题,在E-Learning学业情绪模型中引入性格因素,根据性格、心情和情绪的映射关系,将其融入到基于专注度、趋避度、愉悦度的三维学业情绪空间中,建立融合性格因素的基于遗传算法优化径向基函数神经网络(RBF)的E-Learning学业情绪模型,为E-Learning情境中结合人的性格和心情研究情绪认知评价问题提供一种可能。实验结果表明,该模型具有较高的识别率和较好的实时性。Traditional emotional models lack personality factors,to overcome this limitation,personality was considered in E-Learning academic emotion model,the mapping among personality,mood and emotion was established,and the corresponding parameters were quantified for academic emotion model based on the degree of approach-avoidance,degree of attention and degree of pleasure.Genetic algorithms improved radial basis function neural network was used to establish E-Learning academic emotion model with personality integrated.It provided a possible combination of personality and mood to resolve emotional cognitive evaluation in E-Learning.Experimental results show that this model has high recognition rate and timeliness characteristic.

关 键 词：E-Learning情境 情绪认知评价 遗传算法 RBF神经网络 性格 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]