A prediction model for the unemployment rate of college graduates was developed based on principal component analysis and BP neural network, followed by analyzing the unemployment data of college graduates in Hebei province in the years 1995—2016.The results show that the model can effectively reflect the variation tendency of the unemployment rate of college graduates in Hebei province and the prediction accuracy of the model is higher than that of the model only based on BP neural network.
LIU Zhao
. Empirical study on a prediction model for the unemployment rate of college graduates based on principal component analysis and BP neural network[J]. Journal of Hebei University(Natural Science Edition), 2018
, 38(1)
: 99
-104
.
DOI: 10.3969/j.issn.1000-1565.2018.01.015
[1] 王先述.基于Cramer法则和ARMA模型的我国高校毕业生就业预测[J].统计与决策, 2010(22):97-99.DOI:10.13546/j.cnki.tjyjc.2010.22.014. WANG X S.Employment forecast of college graduates in China based on Cramer rule and ARMA model[J].Statistics & Decision, 2010(22):97-99.DOI:10.13546/j.cnki.tjyjc.2010.22.014.
[2] 叶苗.大数据分析大学生就业率估计模型仿真[J].计算机仿真, 2016,33(11):183-186. YE M.Big data analysis of college students' employment rate estimation model simulation[J].Computer Simulation, 2016,33(11):183-186.
[3] 沈国琪,陈万明.基于多元线性回归与BP神经网络分析的失业预测建模实证研究[J].工业技术经济, 2014,33(02):103-112.DOI:10.3969/j.issn.1004-910X.2014.02.013. SHEN G Q, CHEN W M.Empirical research on modeling of unemployment forecast-based on multiple linear regression and BP neural network[J].Journal of Industrial Technological Economics, 2014,33(02):103-112.DOI:10.3969/j.issn.1004-910X.2014.02.013.
[4] 李宏,李建武,宋玉龙.基于神经网络集成的失业预警方法[J].经济与管理研究, 2012,(01):89-94.DOI:10.13502/j.cnki.issn1000-7636.2012.01.005. LI H, LI J W, SONG Y L.Unemployment early-warning based on neural network ensembles[J].Research on Economics and Management, 2012,(01):89-94.DOI:10.13502/j.cnki.issn1000-7636.2012.01.005.
[5] OLMEDO E.Forecasting Spanish unemployment using near neighbour and neural net techniques[J].Computational Economics, 2014,43:183-197.DOI:10.1007/s10614-013-9371-1.
[6] STASINAKIS C, SERMPINIS G, THEOFILATOS K, et al.Forecasting US unemployment with radial basis neural networks, Kalman filters and support vector regressions[J].Computational Economics, 2016,47:569-587.DOI:10.1007/s10614-014-9479-y.
[7] 邹治.高校毕业生失业预警系统研究[D].南京:南京航空航天大学, 2012. ZOU Z.Research on early-warning system of unemployment of college graduates[D].Nanjing:Nanjing University of Aeronautics and Astronautics, 2012.
[8] TRAPPEY A J C, TRAPPEY C V, MA L, et al.Intelligent engineering asset management system for power transformer maintenance decision supports under various operating conditions[J].Computers & Industrial Engineering, 2015,84:3-11.DOI:10.1016/j.cie.2014.12.033.
[9] 刘英华.基于主成分分析与BP神经网络的网络流量预测[J].激光杂志, 2015,36(06):151-153.DOI:10.14016/j.cnki.jgzz.2015.06.151. LIU Y H.Network flow prediction based on principal component analysis and BP neural network[J].Laser Journal, 2015,36(06):151-153.DOI:10.14016/j.cnki.jgzz.2015.06.151.
[10] 王小川,史峰,郁磊,等.MATLAB神经网络43个案例分析[M].北京:北京航空航天大学出版社, 2013. WANG X C, SHI F, YU L, et al.Analysis of 43 cases based on MATLAB neural network[M].Beijing:Beihang University Press, 2013.
[11] KARDAN A A, SADEGHI H, GHIDARY S S, et al.Prediction of student course selection in online higher education institutes using neural network[J].Computers & Education, 2013,65:1-11.DOI:10.1016/j.compedu.2013.01.015.
[12] 付艳茹.基于BP神经网络的高知识群体失业率预测研究[J].吉林师范大学学报(自然科学版), 2012,33(02):125-129.DOI:10.16862/j.cnki.issn1674-3873.2012.02.036. FU Y R.Research on forecast unemployment rate of high knowledge group based on BP neural network[J].Journal of Jilin Normal University(Natural Science Edition), 2012,33(02):125-129.DOI:10.16862/j.cnki.issn1674-3873.2012.02.036.
