Yang, Z. and Qiu, H., 2020. Prediction algorithm of bridge construction cost based on regression analysis. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 979–982. Coconut Creek (Florida), ISSN 0749-0208.

In the prediction of bridge construction cost, the correlation between the variables that affect the construction cost is an important factor that affects the prediction results. In the previous prediction algorithm, there is the problem of low Pearson correlation coefficient. Therefore, the prediction algorithm of bridge construction cost based on regression analysis is designed. According to the structure of the bridge entity and the various costs in the project, the influencing factors of the construction cost of the bridge project are determined, and the determinable coefficients among the influencing factors are calculated by regression analysis, then the predicted value of the construction cost of the bridge project is calculated, and the average relative error method and the mean square deviation ratio method are set to ensure the reliability of the predicted value. The experimental results show that the Pearson correlation coefficient of the designed prediction algorithm based on regression analysis is higher than that of the traditional prediction algorithm, which shows that the algorithm is suitable for practical bridge engineering projects.