基于GBDT回归的空心村常住人口预测算法研究

为解决乡村振兴战略规划下空心村常住人口预测问题,为国家促进乡村发展、乡村建设、乡村治理提供辅助决策。本文采用GBDT回归算法利用电力、气象等数据对空心村常住人口进行预测。通过特征值重要性分析分析方法筛选出空心村常住人口相关性最强的5个特征,针对这些特征采用模型训练及预测的方式预测空心村常住人口。完成数据预处理后,本文采用5折交叉验证法,以3:1:1的比例将数据集分别划分为训练集、交叉验证集和预测集,获取常住人口预测结果后,并采用均方误差和R方值结合可视化方法对于预测结果进行准确性验证。验证结果表明,采用基于GBDT回归的空心村常住人口预测算法对于空心村常住人口有较好的预测结果。

Research on the resident population prediction algorithm of Hollow Village based on GBDT regression

To solve the rural revitalization of the hollow village resident population prediction problem of the strategic planning, for the state promotes the development of rural, rural construction, rural governance provide auxiliary reference. In this paper, GBDT regression algorithm is used to predict the permanent resident population of hollow village by using electricity and meteorological data. Five characteristics with the strongest correlation between the permanent population of hollow village were screened by eigenvalue importance analysis, and model training and prediction were used to predict the permanent population of hollow village according to these characteristics. In this paper, the data set is divided into training set, cross validation set and prediction set in the ratio of 3:1:1 by using the five-fold cross validation method. After obtaining the prediction results of permanent population, the accuracy of the prediction results was verified by means of mean square error and R square value combined with visualization method. The verification results show that the GBDT regression based permanent resident population prediction algorithm has a good prediction result for the permanent resident population of the hollow village.