基于数据挖掘的公路建设对经济增长的贡献分析

Analysis on the Contribution of Highway Construction to Economic Growth Based on Data Mining

为分析公路建设投资、就业人员受教育程度对经济总量及经济结构的贡献度,运用SPSS Modeler软件,以神经网络构建数据挖掘模型进行预测,并对中国2002—2015年公路建设数据进行了分析。结果表明,公路建设投资对第三产业增加值的贡献度最大,为14%;公路就业人员按受教育程度划分,对国内生产总值贡献最大的是研究生(16%);未上过学、小学、大学专科对国内生产总值、第一产业增加值、第二产业增加值的贡献度相差不大。

To analyze the contribution of investment in highway construction,the education level of employees to the total economic output and economic structure,SPSS Modeler software was adapted to build a data mining model based on neural network to forecast and China's highway construction data from 2002 to 2015 were analyzed.The results show that:highway construction investment contributes to the added value of tertiary industry is the largestand the contribution is 14%;For road workers divided by education level,graduate students contribute the most to GDP(16%);For the contributions of who did not receive education,got primary school diploma or college diploma to GDP,the added value of the first industry and the added value of the secondary industry are almost the same.