摘要
就业是一个非常重要的社会和经济统计指标.世界各国政府都非常重视就业问题,将增加就业率作为政府的工作目标.要想解决就业矛盾,就应该对就业问题的未来发展趋势有一个清醒的认识,从而做出正确的决策.本文提出了一种基于因果关系理论、协整理论用于控制与预测的改进BP神经网络,并将其应用于陕西省就业的控制和预测中.
Employment is very important statistics index to society and economy. The government of any country in the world pays attention to tbe problem of employment, all of them have the goal to increase the rate of employment, If we want to solve the employment contradiction well, we should understand clearly the developments trend in the future of the employment problem, thus we can make correct decision on the basis of this. The article proposes an improved BP neural network based on causality theories and coitegration theories that can be used to control and forecast for dependent variable, and it is applied to control and forecast for Sbanxi employment.
出处
《数学的实践与认识》
CSCD
北大核心
2006年第9期271-275,共5页
Mathematics in Practice and Theory
基金
陕西省教育厅专项基金(01JK133)
校青年基金(00QN21)
关键词
因果关系理论
协整理论
BP神经网络
就业
causality theories
cointegration theories
P neural network
employment
