摘要
为使上传的微视频更加符合现代教学需求,进行思政学习资源上传系统微视频功能设计。分析各类用户拥有的权限,根据学生接收知识能力与综合素质的差异,分类学习风格,利用贝叶斯网络,视每个学生为一个向量,将感知、认知与人格三个维度作为节点,通过推算不同节点之间依赖关系,构建贝叶斯网络学习风格模型;在流媒体自动传输基础上,使用带宽自适应调节算法根据信道状况自动调节视频上传速率。仿真实验表明,使用该方法设计的微视频上传自动化程度高,避免信道拥堵,可以减少资源应用延时。
In order to make the uploaded micro video meet the needs of modern teaching, the micro video function design of the upload system of ideological and political learning resources is carried out. According to the differences of students’ ability to receive knowledge and comprehensive quality, learning styles are classified. Using Bayesian network, each student is regarded as a vector, and the three dimensions of perception, cognition and personality are taken as nodes. By calculating the dependence between different nodes, the learning style model of Bayesian network is constructed In addition, the bandwidth adaptive adjustment algorithm is used to automatically adjust the video upload rate according to the channel conditions. Simulation results show that the micro video upload designed by this method has high degree of automation, avoids channel congestion and can reduce resource application delay.
作者
王颖
WANG Ying(Xi'an Vocational and Technical College,Xi'an 710077 China)
出处
《自动化技术与应用》
2023年第1期138-142,共5页
Techniques of Automation and Applications
关键词
资源上传
微视频
贝叶斯网络
带宽自适应算法
resources upload
micro video
bayesian network
bandwidth adaptive algorithm
