基于BP神经网络的福州市人口预测模型

Prediction Model of Population in Fuzhou City Based on BP Neural Network

根据福州市区1981-2004年的人口统计数据,应用BP-MSM算法,建立福州市区BP神经网络的时间序列预测模型,并与一元线性回归模型、人口自然增长模型、指数函数模型、幂函数模型、马尔萨斯人口增长模型、Logistic人口预测模型的预测结果进行比较,结果表明BP神经网络对人口数量的预测精度更高,效果更好.

Based on the statistics about the population from 1981 to 2004, and using BP-MSM, the paper establishes the time series model of population prediction of Fuzhou city based on BPNN, and compares with the other traditional models such as linear regression model, natural population growth model, the index model, the power model, Malthusian population growth model, and logistic population prediction model, etc. The result shows that BPNN model is more precise and effective.