摘要
为了落实高校贫困学生的资助工作,将BP神经网络和SVC技术应用于高校贫困生的评定领域。因为在高校贫困生评定领域,各高校的做法均有不同,难以有统一规范的参考标准。为了满足实际需求,提高数据预测和分类的能力,提出一个科学、准确的评定方法。具体包括如下技术:BP神经网络预测、SVC技术预测,最后在实际数据中予以验证预测效果。
In order to implement the aid work of poor college students, applies BP neural network and SVC technology to the evaluation of poor college students. In the field of evaluation of poor students in colleges and universities, the practice of each university is different, and it is difficult to have a uniform and standardized reference standard. In order to meet the practical needs and improve the ability of data prediction and classification, proposes a scientific and accurate evaluation method. Including the following techniques: BP neural network prediction, SVC technology prediction, finally in the actual data to verify the prediction effect.
作者
冯文文
郭燎原
魏雨
张兴隆
郭春兰
FENG Wen-wen;GUO Liao-yuan;WEI Yu;ZHANG Xing-long;GUO Chun-lan(College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007)
出处
《现代计算机》
2019年第18期36-39,46,共5页
Modern Computer
关键词
BP神经网络
SVC技术
贫困生评定
BP Neural Network
SVC Technology
Assessment of Poor Student