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公路工程人工费调整应结合国家经济水平、就业规模、消费物价指数等诸多复杂因素的变化,把这些影响因子导入matlable软件进行拟合,得出拟合图像及相关系数,发现公路工程人工工日单价和人均DGP、CPI、建筑业劳动生产率有很强的相关性,与建筑业就业规模有较强的相关性。本文选择这4个影响因子作为目标值与公路工程人工工日单价建立多元线性回归模型。同时根据历史数据对人均DGP、CPI、建筑业劳动生产率、建筑业就业规模建立时间序列模型用于预测未来数年公路工程人工工日单价。
The labor cost adjustment of highway engineering should be combined with the changes of many complicated factors such as the national economic level, employment scale and consumer price index. These influencing factors are introduced into the matlable software to get the fitting image and the correlation coefficient, and the results of artificial engineering day Unit price and per capita DGP, CPI, construction labor productivity has a strong correlation with the scale of employment in the construction industry has a strong correlation. In this paper, the four influencing factors are selected as the target value to establish multivariate linear regression model with highway engineering artificial daily price. At the same time, a time series model of per capita DGP, CPI, labor productivity of construction industry and employment scale of construction industry is established based on historical data to predict the unit price of artificial daily man-days of highway engineering in the next few years.