摘要
以我国X高校贫困生为研究对象,在获取其个人、家庭、家乡、就业相关信息的基础上,采用模糊隶属度函数法将定性返乡影响因素定量化,引入基于二元萤火虫算法的分形维数属性选择方法,分析得出高校贫困生返乡就业的关键影响因素为父母因素、生活成本、薪资待遇、发展机会等,并采用支持向量机验证其合理性,最后为有效引导高校贫困生返乡提出建议和发展思路.
Taking the poor students of X College in our country as a case,the personal,family,hometown,employment information is collected from a large range of sources.Firstly,fuzzy membership function is involved to put the qualitative influencing factors of returning home quantitatively,and then Binary Glowworm Swarm Optimization(BGSO)combined with Fractal Dimension is introduced,and the key factors include parents,living costs,wage,career possibilities which influence the poor college students returning home for employment are mined.Secondly,support vector machine is used to certify their correctness.Finally,feasible suggestions and development ideas for guiding poor students to return home are presented.
作者
程美英
周建华
钱乾
CHENG Meiying;ZHOU Jianhua;QIAN Qian(School of Business, Huzhou University, Huzhou 313000, China;School of Teacher Education, Huzhou University, Huzhou 313000, China)
出处
《湖州师范学院学报》
2020年第4期97-103,共7页
Journal of Huzhou University
基金
教育部人文社科规划基金项目(18YJAZH144)
浙江省教育科学规划课题(2019SCG036)
浙江省高等教育“十三五”第二批教学改革项目(jg20190652)
浙江省人力资源和社会保障科学研究课题(2019088)
湖州市自然科学基金项目(2018YZ11).
关键词
高校贫困生
返乡就业
影响因素
二元萤火虫算法(BGSO)
分形维数(FD)
poor college students
returning home for employment
influencing factors
Binary Glowworm Swarm Optimization(BGSO)
Fractal Dimension(FD)
