Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

October 23, 2023


Pages


DOI

Article

Research on risk prediction and prevention and control measures of economic management of engineering construction based on econometric model

Check for updates


Authors

Jingsi Yang Affiliation:
Economic and Technological Research Institute, State Grid Heilongjiang Electric Power Co., Ltd., Harbin, Heilongjiang, 150010, China.
, Zhenhai Li Affiliation:
Economic and Technological Research Institute, State Grid Heilongjiang Electric Power Co., Ltd., Harbin, Heilongjiang, 150010, China.
and Ge Yang Affiliation:
Economic and Technological Research Institute, State Grid Heilongjiang Electric Power Co., Ltd., Harbin, Heilongjiang, 150010, China.


Abstract

To provide construction units with comprehensive and accurate information to assist in decision-making, this paper utilizes econometric models to use the Internet for management monitoring and engineering construction schedule scheduling. The parametric linearity constraint test method is set up, production function examples are established for engineering tests, and statistics are approximated to obey degrees of freedom and cardinal distribution. To obtain the inverse of the estimated information matrix, the least squares method is employed to maximize the engineering construction expression. The engineering economic management error value is found to be the lowest value of 0.84, the maximum value of elasticity coefficient is 0.379, and the minimum value of covariance is 0.185. To fully improve the risk prediction capability of engineering construction, econometric modeling techniques must be integrated.


Keywords

Econometric modeling, Parametric linear constraint, Chi-square distribution, Least squares, Risk prediction, 91B44


Citation

Yang, J., Li, Z., & Yang, G. (2023). Research on risk prediction and prevention and control measures of economic management of engineering construction based on econometric model. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.00758

Published by: Engineering Journals

Engineering Journals Logo