相空间重构神经网络模型在我国人口增长预测中的应用

Application on Via Phase Space Reconstruction and Neural Network Model in the Prediction to the Population Increasing

人口系统是一个非常复杂的非线性系统,人口增长是十分重要的人口变化因子,对人口增长的准确预测能为社会经济可持续发展计划的制定提供重要依据.借鉴相空间重构和神经网络,建立了预测我国人口增长的相空间重构神经网络模型.模型运用相空间重构,可挖掘人口增长时间序列更为丰富的信息,利用神经网络建模可较好地解决非线性问题,使预测更符合实际.以我国1950—2002年人口增长数据为例,验证了该模型具有较高的拟和和预报精度,为我国人口增长预测问题提供一种新的解决办法.

The population system is a very complicated nonlinear system,and the population increasing is one of the very important factors to the variety of the population,therefore an accurate prediction of population increasing will be helpful to the planning of sustainable development of the social economy.Prediction model of the local population increasing has been built via by the phase space reconstruction and neural network.More rich information can be discovered by phase space reconstruction,and the nonlinear ...