Open AccessDynamic prediction model of bridge project life cycle cost investment based on decision tree algorithm
Author(s) -
Jing Li,
Xu Li,
Zhuoqun Zhang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/760/1/012049
Subject(s) - bridge (graph theory) , decision tree , decision tree model , computer science , matlab , tree (set theory) , predictive modelling , algorithm , reliability engineering , data mining , engineering , machine learning , mathematics , medicine , mathematical analysis , operating system
In order to further improve the dynamic prediction effect of bridge engineering life cycle cost, a life cycle cost prediction model of bridge engineering is established by using decision tree algorithm, and the influence coefficient of bridge engineering characteristics on cost is analyzed by data acquisition method. After analysis, the project characteristics which have great influence on the cost of bridge engineering are determined. The decision tree algorithm is used to establish the dynamic prediction model of bridge engineering life cycle cost; through MATLAB software, a good bridge cost prediction model is gradually established, and the model is trained, modified and verified according to the actual engineering data. The dynamic prediction model of life cycle cost investment of bridge engineering is established by using decision tree algorithm, which effectively improves the prediction accuracy and has strong practicability.